aramintak/pola-style
pola-style
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aramintak/pola-style
Trigger phrase: Polaroid style
aramintak/soft-ones
A model that makes a soft and quiet world. Can use "daiton" as a trigger but it isn't needed.
aramintak/pop-art-anime
A very blocky and bold cartoon style with some anime elements. You should use daiton style to trigger the image generation.
aramintak/araminta-k-illustration
A style model, ligne claire esque with eastern influence
aramintak/abstract-anime-painting
A style that creates a paint wash, great for anime.
aramintak/gemini-anime
An anime style
aramintak/soft-pastel-anime
Stylized sketch anime model that has a bit of a watercolor undertone to it
aramintak/painting-light
A watercolor style painting model that does impressionism well and lends itself to anime.
aramintak/lost-and-lonely-manga
A manga style
aramintak/sketched-out-manga
A rough sketch style manga
aramintak/japanese-poster-prints
A mid-century Japanese block print style
aramintak/flux-koda
Flux lora, use "flmft style" to trigger the image generation
aramintak/flux-film-foto
Flux lora in a realistic film style. Use flmft photo style to trigger the image generation.
aramintak/flux-frosting-lane
Flux lora, use "frstingln illustration" to trigger the image generation
aramintak/flux-softserve-anime
Flux lora, use "sftsrv style illustration" to trigger the image generation
aramintak/linnea-flux-beta
An original character LoRA
aramintak/enna-sketch-style
A hand drawn sketch style LoRA
aramintak/mooniverse
Trigger phrase: surreal style
aramintak/dreamcore-wan
aramintak/ettienne-tarot-style
aramintak/the_point_wan2
Illustration style model with gritty depth.
Prediction
aramintak/pola-style:def181881b9a46c435b8a73baa906de9c0c2fb9b9c0716f31dc38c3a48fa2e89ID4tc8rrjyk1rm20cj2tbrp5k978StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a girl laughing, polaroid style
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a girl laughing, polaroid style", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:def181881b9a46c435b8a73baa906de9c0c2fb9b9c0716f31dc38c3a48fa2e89", { input: { model: "dev", prompt: "a girl laughing, polaroid style", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:def181881b9a46c435b8a73baa906de9c0c2fb9b9c0716f31dc38c3a48fa2e89", input={ "model": "dev", "prompt": "a girl laughing, polaroid style", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:def181881b9a46c435b8a73baa906de9c0c2fb9b9c0716f31dc38c3a48fa2e89", "input": { "model": "dev", "prompt": "a girl laughing, polaroid style", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-21T21:59:26.213684Z", "created_at": "2024-09-21T21:57:51.896000Z", "data_removed": false, "error": null, "id": "4tc8rrjyk1rm20cj2tbrp5k978", "input": { "model": "dev", "prompt": "a girl laughing, polaroid style", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 43712\nPrompt: a girl laughing, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=6624785854464\nDownloading weights\n2024-09-21T21:58:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv2hv6qp4/weights url=https://replicate.delivery/yhqm/gZfePNb6kFhImkp77cf44zOCUSEj4ceF6gE8HtlBWe2ZF35bC/trained_model.tar\n2024-09-21T21:59:02Z | INFO | [ Complete ] dest=/tmp/tmpv2hv6qp4/weights size=\"462 MB\" total_elapsed=3.353s url=https://replicate.delivery/yhqm/gZfePNb6kFhImkp77cf44zOCUSEj4ceF6gE8HtlBWe2ZF35bC/trained_model.tar\nDownloaded weights in 3.40s\nLoaded LoRAs in 17.89s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:08, 3.29it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.72it/s]\n 11%|█ | 3/28 [00:00<00:07, 3.51it/s]\n 14%|█▍ | 4/28 [00:01<00:07, 3.42it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.37it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.34it/s]\n 25%|██▌ | 7/28 [00:02<00:06, 3.33it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 3.32it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.31it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.30it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 3.30it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.30it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.29it/s]\n 50%|█████ | 14/28 [00:04<00:04, 3.29it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.29it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.29it/s]\n 61%|██████ | 17/28 [00:05<00:03, 3.29it/s]\n 64%|██████▍ | 18/28 [00:05<00:03, 3.29it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.29it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 3.29it/s]\n 75%|███████▌ | 21/28 [00:06<00:02, 3.29it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.29it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.29it/s]\n 86%|████████▌ | 24/28 [00:07<00:01, 3.29it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.29it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.29it/s]\n 96%|█████████▋| 27/28 [00:08<00:00, 3.28it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.28it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.31it/s]", "metrics": { "predict_time": 26.892301235, "total_time": 94.317684 }, "output": [ "https://replicate.delivery/yhqm/XtOfme6TvopCHk8EDVBdjLfYeH98juZNV2yRKjkI2Nq6788NB/out-0.webp" ], "started_at": "2024-09-21T21:58:59.321383Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4tc8rrjyk1rm20cj2tbrp5k978", "cancel": "https://api.replicate.com/v1/predictions/4tc8rrjyk1rm20cj2tbrp5k978/cancel" }, "version": "def181881b9a46c435b8a73baa906de9c0c2fb9b9c0716f31dc38c3a48fa2e89" }Generated inUsing seed: 43712 Prompt: a girl laughing, polaroid style [!] txt2img mode Using dev model free=6624785854464 Downloading weights 2024-09-21T21:58:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv2hv6qp4/weights url=https://replicate.delivery/yhqm/gZfePNb6kFhImkp77cf44zOCUSEj4ceF6gE8HtlBWe2ZF35bC/trained_model.tar 2024-09-21T21:59:02Z | INFO | [ Complete ] dest=/tmp/tmpv2hv6qp4/weights size="462 MB" total_elapsed=3.353s url=https://replicate.delivery/yhqm/gZfePNb6kFhImkp77cf44zOCUSEj4ceF6gE8HtlBWe2ZF35bC/trained_model.tar Downloaded weights in 3.40s Loaded LoRAs in 17.89s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:08, 3.29it/s] 7%|▋ | 2/28 [00:00<00:06, 3.72it/s] 11%|█ | 3/28 [00:00<00:07, 3.51it/s] 14%|█▍ | 4/28 [00:01<00:07, 3.42it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.37it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.34it/s] 25%|██▌ | 7/28 [00:02<00:06, 3.33it/s] 29%|██▊ | 8/28 [00:02<00:06, 3.32it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.31it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.30it/s] 39%|███▉ | 11/28 [00:03<00:05, 3.30it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.30it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.29it/s] 50%|█████ | 14/28 [00:04<00:04, 3.29it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.29it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.29it/s] 61%|██████ | 17/28 [00:05<00:03, 3.29it/s] 64%|██████▍ | 18/28 [00:05<00:03, 3.29it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.29it/s] 71%|███████▏ | 20/28 [00:06<00:02, 3.29it/s] 75%|███████▌ | 21/28 [00:06<00:02, 3.29it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.29it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.29it/s] 86%|████████▌ | 24/28 [00:07<00:01, 3.29it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.29it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.29it/s] 96%|█████████▋| 27/28 [00:08<00:00, 3.28it/s] 100%|██████████| 28/28 [00:08<00:00, 3.28it/s] 100%|██████████| 28/28 [00:08<00:00, 3.31it/s]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDqb8rdndz9drm20cj3519negyb0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:25:16.659785Z", "created_at": "2024-09-22T10:24:17.739000Z", "data_removed": false, "error": null, "id": "qb8rdndz9drm20cj3519negyb0", "input": { "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 24023\nPrompt: A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=7953882656768\nDownloading weights\n2024-09-22T10:24:20Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpx6o95ddd/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:24:23Z | INFO | [ Complete ] dest=/tmp/tmpx6o95ddd/weights size=\"462 MB\" total_elapsed=3.326s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 3.38s\nLoaded LoRAs in 22.90s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.06s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 56.082145181, "total_time": 58.920785 }, "output": [ "https://replicate.delivery/yhqm/zYuU4HGdyI7VNJfxQGFfIMPAvyN9WIAlAbwQvjk8CgKMKafmA/out-0.webp", "https://replicate.delivery/yhqm/dNF2BBf74EUsACYdNr9ewwqQY1m4Gd3WNs5QoddvpjTMKafmA/out-1.webp", "https://replicate.delivery/yhqm/3Uafg1J9NNSoCKdL9Lv7q6sI6XA8oarP0CRr8RHavHLGFtvJA/out-2.webp", "https://replicate.delivery/yhqm/pldUDzDJyx4eM6c1tfBoZeBb65vKpJNeeHuuZf8OPXAMji23E/out-3.webp" ], "started_at": "2024-09-22T10:24:20.577640Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/qb8rdndz9drm20cj3519negyb0", "cancel": "https://api.replicate.com/v1/predictions/qb8rdndz9drm20cj3519negyb0/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 24023 Prompt: A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, polaroid style [!] txt2img mode Using dev model free=7953882656768 Downloading weights 2024-09-22T10:24:20Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpx6o95ddd/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:24:23Z | INFO | [ Complete ] dest=/tmp/tmpx6o95ddd/weights size="462 MB" total_elapsed=3.326s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 3.38s Loaded LoRAs in 22.90s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.06s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDtnxffernq9rm20cj35298s0pdwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:26:47.197266Z", "created_at": "2024-09-22T10:25:45.402000Z", "data_removed": false, "error": null, "id": "tnxffernq9rm20cj35298s0pdw", "input": { "model": "dev", "prompt": "A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 12959\nPrompt: A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=6583963889664\nDownloading weights\n2024-09-22T10:25:58Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptanpies6/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:26:00Z | INFO | [ Complete ] dest=/tmp/tmptanpies6/weights size=\"462 MB\" total_elapsed=1.507s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.55s\nLoaded LoRAs in 15.63s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 48.696478185, "total_time": 61.795266 }, "output": [ "https://replicate.delivery/yhqm/Kmv7puJD5tYIBZa65f37kPluDsoS6j6opeevZM05PPLNX0eNB/out-0.webp", "https://replicate.delivery/yhqm/gHt3i3sYGc5jCBrjeiN7q72prR5bAtXSrfedETjWfaRZuo9NB/out-1.webp", "https://replicate.delivery/yhqm/KmBomV5Tm2ZFHxkMfazRBMaJu4UWp9OEPUqTZdalLejmLafmA/out-2.webp", "https://replicate.delivery/yhqm/2lPb8yQkmg5jAdqDBFIZ0HuyQmrFPeuPHVBchMCVrJmzFtvJA/out-3.webp" ], "started_at": "2024-09-22T10:25:58.500788Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tnxffernq9rm20cj35298s0pdw", "cancel": "https://api.replicate.com/v1/predictions/tnxffernq9rm20cj35298s0pdw/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 12959 Prompt: A tabby cat lounging on a sun-dappled windowsill, faded, polaroid style [!] txt2img mode Using dev model free=6583963889664 Downloading weights 2024-09-22T10:25:58Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmptanpies6/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:26:00Z | INFO | [ Complete ] dest=/tmp/tmptanpies6/weights size="462 MB" total_elapsed=1.507s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.55s Loaded LoRAs in 15.63s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDxys00f9vq1rm40cj352sbne49wStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- woman, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "woman, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "woman, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "woman, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "woman, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:28:12.663478Z", "created_at": "2024-09-22T10:27:00.664000Z", "data_removed": false, "error": null, "id": "xys00f9vq1rm40cj352sbne49w", "input": { "model": "dev", "prompt": "woman, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 9131\nPrompt: woman, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=6833853698048\nDownloading weights\n2024-09-22T10:27:21Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvp_qb2c8/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:27:24Z | INFO | [ Complete ] dest=/tmp/tmpvp_qb2c8/weights size=\"462 MB\" total_elapsed=3.133s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 3.19s\nLoaded LoRAs in 18.36s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 51.290427747, "total_time": 71.999478 }, "output": [ "https://replicate.delivery/yhqm/kA46GgkgFc5dCtqwy1RV8kQWjbE5QNvOjMo002VKksMPj23E/out-0.webp", "https://replicate.delivery/yhqm/XnP6z1sEM5pUFJz4FppG7fWDQKf7P6c5XEtBpzAYPSR8MafmA/out-1.webp", "https://replicate.delivery/yhqm/0fHfakHtWdpB2U87izup1e5LeHFLNCFfi4GRc6COeefV8MafmA/out-2.webp", "https://replicate.delivery/yhqm/GwPWjeLyTOzjVyvFH8CwZhNEvfcJNs1c0uUdFs6eIRW5Z0eNB/out-3.webp" ], "started_at": "2024-09-22T10:27:21.373050Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xys00f9vq1rm40cj352sbne49w", "cancel": "https://api.replicate.com/v1/predictions/xys00f9vq1rm40cj352sbne49w/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 9131 Prompt: woman, polaroid style [!] txt2img mode Using dev model free=6833853698048 Downloading weights 2024-09-22T10:27:21Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpvp_qb2c8/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:27:24Z | INFO | [ Complete ] dest=/tmp/tmpvp_qb2c8/weights size="462 MB" total_elapsed=3.133s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 3.19s Loaded LoRAs in 18.36s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDzqnzpqp0c9rm20cj353aze65smStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Road trip, view through car window of desert highway, light leak effect, polaroid style style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Road trip, view through car window of desert highway, light leak effect, polaroid style style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "Road trip, view through car window of desert highway, light leak effect, polaroid style style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "Road trip, view through car window of desert highway, light leak effect, polaroid style style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "Road trip, view through car window of desert highway, light leak effect, polaroid style style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:29:29.750715Z", "created_at": "2024-09-22T10:28:40.162000Z", "data_removed": false, "error": null, "id": "zqnzpqp0c9rm20cj353aze65sm", "input": { "model": "dev", "prompt": "Road trip, view through car window of desert highway, light leak effect, polaroid style style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 276\nPrompt: Road trip, view through car window of desert highway, light leak effect, polaroid style style\n[!] txt2img mode\nUsing dev model\nfree=9119141801984\nDownloading weights\n2024-09-22T10:28:40Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp6phxjy4u/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:28:43Z | INFO | [ Complete ] dest=/tmp/tmp6phxjy4u/weights size=\"462 MB\" total_elapsed=3.303s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 3.35s\nLoaded LoRAs in 16.66s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 49.57388277, "total_time": 49.588715 }, "output": [ "https://replicate.delivery/yhqm/8GuXZC1gRP6xLFadlf3CCBJXFasBPPyod92Es4C0YSzEHtvJA/out-0.webp", "https://replicate.delivery/yhqm/f2lB9a3R44WwO68C61TVg0zf94SmGb8BHfAHOH44ofIm4o9NB/out-1.webp", "https://replicate.delivery/yhqm/bfhGsqGsDbVpeUC7x6pfEodW8LNFugJVl3QJ3EKtHgfm4o9NB/out-2.webp", "https://replicate.delivery/yhqm/9BKG5cz8FXLwJ19tB5R2JNzAe2sp6ewvkwaowTlHt1iJOafmA/out-3.webp" ], "started_at": "2024-09-22T10:28:40.176832Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zqnzpqp0c9rm20cj353aze65sm", "cancel": "https://api.replicate.com/v1/predictions/zqnzpqp0c9rm20cj353aze65sm/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 276 Prompt: Road trip, view through car window of desert highway, light leak effect, polaroid style style [!] txt2img mode Using dev model free=9119141801984 Downloading weights 2024-09-22T10:28:40Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp6phxjy4u/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:28:43Z | INFO | [ Complete ] dest=/tmp/tmp6phxjy4u/weights size="462 MB" total_elapsed=3.303s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 3.35s Loaded LoRAs in 16.66s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID0asfgnf6nxrm60cj353sjaa41cStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:30:42.505295Z", "created_at": "2024-09-22T10:29:55.503000Z", "data_removed": false, "error": null, "id": "0asfgnf6nxrm60cj353sjaa41c", "input": { "model": "dev", "prompt": "the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 3393\nPrompt: the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 13.94s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 46.994679965, "total_time": 47.002295 }, "output": [ "https://replicate.delivery/yhqm/rU8ZAn145UJZNpmNz6i4u9fl4GGAQ7MBxuzsz0utzxApHtvJA/out-0.webp", "https://replicate.delivery/yhqm/fMW2oeZujHn8R0veoCXagneRleME0R6H3SGMgECOBvHX6R7bC/out-1.webp", "https://replicate.delivery/yhqm/tQKB9aLhgD48LBzBlBdnL5jt310oc9P9LFQvPV9gOeCpHtvJA/out-2.webp", "https://replicate.delivery/yhqm/welCcvmEGIXLKSql1Z1zeCx5HieduQYC8bwd9SMLxYUleo9NB/out-3.webp" ], "started_at": "2024-09-22T10:29:55.510615Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/0asfgnf6nxrm60cj353sjaa41c", "cancel": "https://api.replicate.com/v1/predictions/0asfgnf6nxrm60cj353sjaa41c/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 3393 Prompt: the morning after new years eve with scattered party tinsel on the floor, still life, light particles, no humans, polaroid style [!] txt2img mode Using dev model Loaded LoRAs in 13.94s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID6fvtsfbadsrm60cj354r3xpxbwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- Teenage bedroom with posters and clutter, warm color palette, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "Teenage bedroom with posters and clutter, warm color palette, polaroid style ", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "Teenage bedroom with posters and clutter, warm color palette, polaroid style ", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "Teenage bedroom with posters and clutter, warm color palette, polaroid style ", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "Teenage bedroom with posters and clutter, warm color palette, polaroid style ", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:33:55.290526Z", "created_at": "2024-09-22T10:31:34.766000Z", "data_removed": false, "error": null, "id": "6fvtsfbadsrm60cj354r3xpxbw", "input": { "model": "dev", "prompt": "Teenage bedroom with posters and clutter, warm color palette, polaroid style ", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 57949\nPrompt: Teenage bedroom with posters and clutter, warm color palette, polaroid style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 21.41s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 54.438393068, "total_time": 140.524526 }, "output": [ "https://replicate.delivery/yhqm/6ePWeIWEVUidg0J6OJsq6R7DwWNXcPe1q58ru8BLqOFkk0eNB/out-0.webp", "https://replicate.delivery/yhqm/vLUul30eMaWoayI0r6wRuebbI2aRsJrStagb7zGD3xenk0eNB/out-1.webp", "https://replicate.delivery/yhqm/hSrmb5m07trjA1IuQsEn3lup0mXS33eVedNshqOylsmTSafmA/out-2.webp", "https://replicate.delivery/yhqm/y5MiBzmtAu79HpUSBmGexIRkvy2IT41RMyZVIBaoe6gTSafmA/out-3.webp" ], "started_at": "2024-09-22T10:33:00.852133Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/6fvtsfbadsrm60cj354r3xpxbw", "cancel": "https://api.replicate.com/v1/predictions/6fvtsfbadsrm60cj354r3xpxbw/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 57949 Prompt: Teenage bedroom with posters and clutter, warm color palette, polaroid style [!] txt2img mode Using dev model Loaded LoRAs in 21.41s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDngb3g57nhsrm40cj355r1xya7rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:35:08.768152Z", "created_at": "2024-09-22T10:34:21.454000Z", "data_removed": false, "error": null, "id": "ngb3g57nhsrm40cj355r1xya7r", "input": { "model": "dev", "prompt": "A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 22471\nPrompt: A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=7476212371456\nDownloading weights\n2024-09-22T10:34:21Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk6g_no0a/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:34:23Z | INFO | [ Complete ] dest=/tmp/tmpk6g_no0a/weights size=\"462 MB\" total_elapsed=1.511s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.62s\nLoaded LoRAs in 14.18s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 47.302577354, "total_time": 47.314152 }, "output": [ "https://replicate.delivery/yhqm/AG9EwhdjRp7YOhO2x1Sj0vFdfYtVX3oOJxOUyqjLOeAcTafmA/out-0.webp", "https://replicate.delivery/yhqm/R3Wra6hn2rpMD9MeUvreDcCoGQbZALVySmVY554wgRacTafmA/out-1.webp", "https://replicate.delivery/yhqm/lpObMfM4ZVWqNyeC70C4Yw3cA3rAIIC5cm7XcWirfsn4m0eNB/out-2.webp", "https://replicate.delivery/yhqm/c6O9Ipx7OjIEOBNs9AqOHdJ6QIvbkBoOClJfGhUKooYuJtvJA/out-3.webp" ], "started_at": "2024-09-22T10:34:21.465574Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ngb3g57nhsrm40cj355r1xya7r", "cancel": "https://api.replicate.com/v1/predictions/ngb3g57nhsrm40cj355r1xya7r/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 22471 Prompt: A young woman with tousled hair and minimal makeup, wearing a oversized flannel shirt, looking directly at the camera with a slight smile. The background is slightly out of focus, suggesting a cozy bedroom, polaroid style [!] txt2img mode Using dev model free=7476212371456 Downloading weights 2024-09-22T10:34:21Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk6g_no0a/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:34:23Z | INFO | [ Complete ] dest=/tmp/tmpk6g_no0a/weights size="462 MB" total_elapsed=1.511s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.62s Loaded LoRAs in 14.18s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDd98dqar1hdrm00cj356spb48n4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- closeup of an eye, pink white and blue, aesthetic polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "closeup of an eye, pink white and blue, aesthetic polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "closeup of an eye, pink white and blue, aesthetic polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "closeup of an eye, pink white and blue, aesthetic polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "closeup of an eye, pink white and blue, aesthetic polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:36:17.610413Z", "created_at": "2024-09-22T10:35:30.059000Z", "data_removed": false, "error": null, "id": "d98dqar1hdrm00cj356spb48n4", "input": { "model": "dev", "prompt": "closeup of an eye, pink white and blue, aesthetic polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 14220\nPrompt: closeup of an eye, pink white and blue, aesthetic polaroid style\n[!] txt2img mode\nUsing dev model\nfree=6896858685440\nDownloading weights\n2024-09-22T10:35:30Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp47m2vam9/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:35:32Z | INFO | [ Complete ] dest=/tmp/tmp47m2vam9/weights size=\"462 MB\" total_elapsed=2.061s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 2.11s\nLoaded LoRAs in 14.61s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 47.542324645, "total_time": 47.551413 }, "output": [ "https://replicate.delivery/yhqm/SFJtTCVQ7BqRGFNtsQ4SN9GlJ3OIfui16e84bkcIJC3hUafmA/out-0.webp", "https://replicate.delivery/yhqm/eDEs38YECAT8biiLmdd0yTGrCrV3LhXqsux1VLfOCe8Cp0eNB/out-1.webp", "https://replicate.delivery/yhqm/cnf0XqxFoSS2NqX7noAlEj3aqd6r6Ozte6ieGzQ5W3PCp0eNB/out-2.webp", "https://replicate.delivery/yhqm/sb0dqiY3W45fDy35XymeH2eYLGiYEfqDTBzyQFpbqz9FSp9NB/out-3.webp" ], "started_at": "2024-09-22T10:35:30.068089Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d98dqar1hdrm00cj356spb48n4", "cancel": "https://api.replicate.com/v1/predictions/d98dqar1hdrm00cj356spb48n4/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 14220 Prompt: closeup of an eye, pink white and blue, aesthetic polaroid style [!] txt2img mode Using dev model free=6896858685440 Downloading weights 2024-09-22T10:35:30Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp47m2vam9/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:35:32Z | INFO | [ Complete ] dest=/tmp/tmp47m2vam9/weights size="462 MB" total_elapsed=2.061s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 2.11s Loaded LoRAs in 14.61s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDhefc68yv2hrm00cj3579e8a8a4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a woman with long red hair smiling, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a woman with long red hair smiling, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a woman with long red hair smiling, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a woman with long red hair smiling, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a woman with long red hair smiling, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:38:38.278791Z", "created_at": "2024-09-22T10:37:31.284000Z", "data_removed": false, "error": null, "id": "hefc68yv2hrm00cj3579e8a8a4", "input": { "model": "dev", "prompt": "a woman with long red hair smiling, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 21784\nPrompt: a woman with long red hair smiling, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=7887031742464\nDownloading weights\n2024-09-22T10:37:31Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgv41qvxu/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:37:32Z | INFO | [ Complete ] dest=/tmp/tmpgv41qvxu/weights size=\"462 MB\" total_elapsed=1.588s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.64s\nLoaded LoRAs in 34.09s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.02it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.04s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it]\n 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.11s/it]", "metrics": { "predict_time": 66.984164864, "total_time": 66.994791 }, "output": [ "https://replicate.delivery/yhqm/l6FQpn4YjP7CJpSMElUI5jdMfCqvufiPC9qHP5o0YIJtWafmA/out-0.webp", "https://replicate.delivery/yhqm/YkAq91WSE1J8BRnOY0KMuOULpdzKP6iCSxXNQJj8iiirl23E/out-1.webp", "https://replicate.delivery/yhqm/1xgdvMOZlDaLKFgGJx0MggefgfhJ6VevfLiEGtu7MQJw1S7bC/out-2.webp", "https://replicate.delivery/yhqm/f8hv3xQIfgpvx0niQS91ebfXunl8NmGxa2S1tGOJSiY6ap9NB/out-3.webp" ], "started_at": "2024-09-22T10:37:31.294626Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/hefc68yv2hrm00cj3579e8a8a4", "cancel": "https://api.replicate.com/v1/predictions/hefc68yv2hrm00cj3579e8a8a4/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 21784 Prompt: a woman with long red hair smiling, polaroid style [!] txt2img mode Using dev model free=7887031742464 Downloading weights 2024-09-22T10:37:31Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpgv41qvxu/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:37:32Z | INFO | [ Complete ] dest=/tmp/tmpgv41qvxu/weights size="462 MB" total_elapsed=1.588s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.64s Loaded LoRAs in 34.09s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.02it/s] 11%|█ | 3/28 [00:03<00:26, 1.04s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it] 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDsakpgjh3xnrm40cj3588qny7v8StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a cute kitten, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a cute kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a cute kitten, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a cute kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a cute kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:39:46.759931Z", "created_at": "2024-09-22T10:38:55.469000Z", "data_removed": false, "error": null, "id": "sakpgjh3xnrm40cj3588qny7v8", "input": { "model": "dev", "prompt": "a cute kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 7932\nPrompt: a cute kitten, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=7782126473216\nDownloading weights\n2024-09-22T10:38:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpr2r613_3/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:39:00Z | INFO | [ Complete ] dest=/tmp/tmpr2r613_3/weights size=\"462 MB\" total_elapsed=1.269s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.31s\nLoaded LoRAs in 14.82s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.02it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.04s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it]\n 36%|███▌ | 10/28 [00:10<00:20, 1.11s/it]\n 39%|███▉ | 11/28 [00:12<00:18, 1.11s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:29<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.11s/it]", "metrics": { "predict_time": 47.517586986, "total_time": 51.290931 }, "output": [ "https://replicate.delivery/yhqm/mUw9MCbN3JKbJpwU4B0VuUgzg7UMrf4nZfduPnOeJlVkv0eNB/out-0.webp", "https://replicate.delivery/yhqm/y9AmPIygET7QOtgxTWBnDiWErfBOnvX7vpfftjcBa27kv0eNB/out-1.webp", "https://replicate.delivery/yhqm/Rqc83dfJW80UekFOR8sy1xPBeyQyfhfFz6N4bbXnDlRSel23E/out-2.webp", "https://replicate.delivery/yhqm/7uzrQqJmBvp1M16KVM8JV06azQXWeAQe3cyjsxC7R6vyXafmA/out-3.webp" ], "started_at": "2024-09-22T10:38:59.242344Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/sakpgjh3xnrm40cj3588qny7v8", "cancel": "https://api.replicate.com/v1/predictions/sakpgjh3xnrm40cj3588qny7v8/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 7932 Prompt: a cute kitten, polaroid style [!] txt2img mode Using dev model free=7782126473216 Downloading weights 2024-09-22T10:38:59Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpr2r613_3/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:39:00Z | INFO | [ Complete ] dest=/tmp/tmpr2r613_3/weights size="462 MB" total_elapsed=1.269s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.31s Loaded LoRAs in 14.82s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.02it/s] 11%|█ | 3/28 [00:03<00:26, 1.04s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it] 36%|███▌ | 10/28 [00:10<00:20, 1.11s/it] 39%|███▉ | 11/28 [00:12<00:18, 1.11s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:29<00:01, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDzhhmq3gnksrm00cj358rfwc4tmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:40:43.823594Z", "created_at": "2024-09-22T10:39:57.342000Z", "data_removed": false, "error": null, "id": "zhhmq3gnksrm00cj358rfwc4tm", "input": { "model": "dev", "prompt": "a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 11935\nPrompt: a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 13.50s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 46.470104144, "total_time": 46.481594 }, "output": [ "https://replicate.delivery/yhqm/INmWfWYgexqFUktIExod3kJWszinc8PIfXomGfR7plefKm23E/out-0.webp", "https://replicate.delivery/yhqm/KlNakheDHT2aM6qaR2li1Q93xP6EGn9JPYfTmlkyibCrYafmA/out-1.webp", "https://replicate.delivery/yhqm/XEFk2wU3B45JF5At23AxLAniuEko8kFGMS48hepGWQwVMtvJA/out-2.webp", "https://replicate.delivery/yhqm/lJvzyvW8MEYtNRRKvVX8HA1rXf4Xdfl4hYo44jxRSkprYafmA/out-3.webp" ], "started_at": "2024-09-22T10:39:57.353489Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zhhmq3gnksrm00cj358rfwc4tm", "cancel": "https://api.replicate.com/v1/predictions/zhhmq3gnksrm00cj358rfwc4tm/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 11935 Prompt: a woman with long blonde hair wearing big round hippie sunglasses with a slight smile, white oversized fur coat, black dress, early evening in the city, polaroid style [!] txt2img mode Using dev model Loaded LoRAs in 13.50s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDgx0j52smsdrm00cj359atsap3mStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "A candid shot of a child\'s hand reaching out to pet a curious deer at a petting zoo. The deer\'s nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:41:59.344247Z", "created_at": "2024-09-22T10:41:10.859000Z", "data_removed": false, "error": null, "id": "gx0j52smsdrm00cj359atsap3m", "input": { "model": "dev", "prompt": "A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 38900\nPrompt: A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=7885125451776\nDownloading weights\n2024-09-22T10:41:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpc0731zhn/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:41:12Z | INFO | [ Complete ] dest=/tmp/tmpc0731zhn/weights size=\"462 MB\" total_elapsed=1.660s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.72s\nLoaded LoRAs in 15.60s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it]\n 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:18, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.11s/it]", "metrics": { "predict_time": 48.47645544, "total_time": 48.485247 }, "output": [ "https://replicate.delivery/yhqm/IepYZkZ8fFo2IUAZtg5fMdCurxVk7UrCWlJAqChmGIDtz0eNB/out-0.webp", "https://replicate.delivery/yhqm/fmDs7DfelEKfOTIfVp66emTDHxohejdsaVHriN8wEaiu7MtvJA/out-1.webp", "https://replicate.delivery/yhqm/fffQx2TXUIe62Rrgkcbx7fdZgBottP6sSYb3KLntwS29OT7bC/out-2.webp", "https://replicate.delivery/yhqm/1msV4NfKSg2XFKWOF9hSlhHK2MQv5lxnZBnYKO9Mo4m7MtvJA/out-3.webp" ], "started_at": "2024-09-22T10:41:10.867791Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/gx0j52smsdrm00cj359atsap3m", "cancel": "https://api.replicate.com/v1/predictions/gx0j52smsdrm00cj359atsap3m/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 38900 Prompt: A candid shot of a child's hand reaching out to pet a curious deer at a petting zoo. The deer's nose is slightly blurred as it moves towards the hand, creating a sense of motion. The background is busy but out of focus, hinting at other animals and visitors, polaroid style [!] txt2img mode Using dev model free=7885125451776 Downloading weights 2024-09-22T10:41:10Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpc0731zhn/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:41:12Z | INFO | [ Complete ] dest=/tmp/tmpc0731zhn/weights size="462 MB" total_elapsed=1.660s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.72s Loaded LoRAs in 15.60s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it] 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:18, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID0x0nv23b6drm00cj359v15vswgStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He\'s wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:43:15.861760Z", "created_at": "2024-09-22T10:42:30.323000Z", "data_removed": false, "error": null, "id": "0x0nv23b6drm00cj359v15vswg", "input": { "model": "dev", "prompt": "A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 1951\nPrompt: A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 12.58s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it]\n 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.11s/it]", "metrics": { "predict_time": 45.531386366, "total_time": 45.53876 }, "output": [ "https://replicate.delivery/yhqm/ZjBdZ7wSn6aOMZ55X2p6eCyfsDuFW5c6flDGK2dlHkeMsp9NB/out-0.webp", "https://replicate.delivery/yhqm/iJWTlAkeAT1CUCvBlXQEFfGGpWae2ZreYFGkvtqnzfIfwm23E/out-1.webp", "https://replicate.delivery/yhqm/Y4XVyR4qizJkCV5NAtlaOdzWIscfbRc2fVKXjBEYFeEG20eNB/out-2.webp", "https://replicate.delivery/yhqm/NWoBlsPnik4LOheJhmUn4g4ybpCbZ5EhCXH7D1yhZNuhNtvJA/out-3.webp" ], "started_at": "2024-09-22T10:42:30.330374Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/0x0nv23b6drm00cj359v15vswg", "cancel": "https://api.replicate.com/v1/predictions/0x0nv23b6drm00cj359v15vswg/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 1951 Prompt: A candid shot of a japanese skateboarder mid-laugh, sitting on the curb of a suburban street. He's wearing a baggy graphic tee, The lighting suggests late afternoon, casting a warm glow on the scene, golden hour, blur, polaroid style [!] txt2img mode Using dev model Loaded LoRAs in 12.58s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it] 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDprt4n76jfhrm00cj35a8b2s8srStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a bottle of water with the text "clean" on it, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a bottle of water with the text \"clean\" on it, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a bottle of water with the text \"clean\" on it, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a bottle of water with the text \"clean\" on it, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a bottle of water with the text \\"clean\\" on it, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:45:11.782585Z", "created_at": "2024-09-22T10:44:02.300000Z", "data_removed": false, "error": null, "id": "prt4n76jfhrm00cj35a8b2s8sr", "input": { "model": "dev", "prompt": "a bottle of water with the text \"clean\" on it, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 52760\nPrompt: a bottle of water with the text \"clean\" on it, polaroid style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 25.14s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.11s/it]", "metrics": { "predict_time": 57.972268467, "total_time": 69.482585 }, "output": [ "https://replicate.delivery/yhqm/qvGS2ZS2G5ZxHdGKAQTLAiyvefofuHObEb1SczkibQxu50eNB/out-0.webp", "https://replicate.delivery/yhqm/AWhHjewnUsUUZC53i7EiK3ga6Z8euUoeNJ9hx58wcoou50eNB/out-1.webp", "https://replicate.delivery/yhqm/G9i0l8Zk5XojBhKuqhUVYx63dliNUDeGA9HXGHtPUk6bOtvJA/out-2.webp", "https://replicate.delivery/yhqm/vIFpOYiZtC6oI9hdapM8GRUsbDsfcQW3aGo61J1Nzfev50eNB/out-3.webp" ], "started_at": "2024-09-22T10:44:13.810317Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/prt4n76jfhrm00cj35a8b2s8sr", "cancel": "https://api.replicate.com/v1/predictions/prt4n76jfhrm00cj35a8b2s8sr/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 52760 Prompt: a bottle of water with the text "clean" on it, polaroid style [!] txt2img mode Using dev model Loaded LoRAs in 25.14s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:10<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDt7dmn9tn9srm20cj35b9aypyscStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a fluffy white kitten, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a fluffy white kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a fluffy white kitten, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a fluffy white kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a fluffy white kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:46:37.733538Z", "created_at": "2024-09-22T10:45:41.326000Z", "data_removed": false, "error": null, "id": "t7dmn9tn9srm20cj35b9aypysc", "input": { "model": "dev", "prompt": "a fluffy white kitten, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 28666\nPrompt: a fluffy white kitten, polaroid style\n[!] txt2img mode\nUsing dev model\nfree=6747783479296\nDownloading weights\n2024-09-22T10:45:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmph7yc2uxn/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:45:51Z | INFO | [ Complete ] dest=/tmp/tmph7yc2uxn/weights size=\"462 MB\" total_elapsed=1.530s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.58s\nLoaded LoRAs in 14.26s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.06s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.13s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.14s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.14s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.14s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.14s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]", "metrics": { "predict_time": 47.433867796, "total_time": 56.407538 }, "output": [ "https://replicate.delivery/yhqm/6BVWPrwDx15ACtNbWLn1O5E9pCTC9Pkg7Q04elWjZLwGPtvJA/out-0.webp", "https://replicate.delivery/yhqm/8P4Moo7TYt7fGCWWr14ETcUCzxHq1m7cG3mPQ5wcR23GPtvJA/out-1.webp", "https://replicate.delivery/yhqm/bcT9vVyWeOygKK5rtm6Iqa2SVOQC8uK8m7wOZyZLXy9GPtvJA/out-2.webp", "https://replicate.delivery/yhqm/L62kpjgeE2R1bCkF1ZfB8JIUQamOfJx1uS0mEul8eRo34p9NB/out-3.webp" ], "started_at": "2024-09-22T10:45:50.299670Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/t7dmn9tn9srm20cj35b9aypysc", "cancel": "https://api.replicate.com/v1/predictions/t7dmn9tn9srm20cj35b9aypysc/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 28666 Prompt: a fluffy white kitten, polaroid style [!] txt2img mode Using dev model free=6747783479296 Downloading weights 2024-09-22T10:45:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmph7yc2uxn/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:45:51Z | INFO | [ Complete ] dest=/tmp/tmph7yc2uxn/weights size="462 MB" total_elapsed=1.530s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.58s Loaded LoRAs in 14.26s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.06s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.13s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:19<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.14s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.14s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.14s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.14s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDpeqjyr4q89rm00cj35bv6r6vscStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a man, polaroid style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a man, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a man, polaroid style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a man, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a man, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:48:09.201990Z", "created_at": "2024-09-22T10:47:03.746000Z", "data_removed": false, "error": null, "id": "peqjyr4q89rm00cj35bv6r6vsc", "input": { "model": "dev", "prompt": "a man, polaroid style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 24282\nPrompt: a man, polaroid style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 13.43s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.12s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]", "metrics": { "predict_time": 46.458984377, "total_time": 65.45599 }, "output": [ "https://replicate.delivery/yhqm/eioVceueZhQrtJ3AMp7AKwCQnUKWFCYoNA7NUebQIcWjeT7bC/out-0.webp", "https://replicate.delivery/yhqm/25UmvfMa0EysF6JfRdMUQ3KW97as8Zsl9p6oWZG9w1Lof0eNB/out-1.webp", "https://replicate.delivery/yhqm/GYEAUQVGJI6lDdiZhuqXx4kfOGV4alR8KiRL779fE4cpf0eNB/out-2.webp", "https://replicate.delivery/yhqm/xmj0snalKnLzHBjuS4m4iN9iRcz3JbRhXCcPJnRiRKc6n23E/out-3.webp" ], "started_at": "2024-09-22T10:47:22.743005Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/peqjyr4q89rm00cj35bv6r6vsc", "cancel": "https://api.replicate.com/v1/predictions/peqjyr4q89rm00cj35bv6r6vsc/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 24282 Prompt: a man, polaroid style [!] txt2img mode Using dev model Loaded LoRAs in 13.43s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.12s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.08s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.11s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.12s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.12s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.12s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.12s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.12s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:18<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.13s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.13s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.13s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID427z880429rm00cj35crrv5xz0StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a gray day with mt fuji in the distance, polaroid photo style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a gray day with mt fuji in the distance, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a gray day with mt fuji in the distance, polaroid photo style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a gray day with mt fuji in the distance, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a gray day with mt fuji in the distance, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:49:25.463309Z", "created_at": "2024-09-22T10:48:37.138000Z", "data_removed": false, "error": null, "id": "427z880429rm00cj35crrv5xz0", "input": { "model": "dev", "prompt": "a gray day with mt fuji in the distance, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 42227\nPrompt: a gray day with mt fuji in the distance, polaroid photo style\n[!] txt2img mode\nUsing dev model\nfree=7969735966720\nDownloading weights\n2024-09-22T10:48:37Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpx5q83vtf/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:48:38Z | INFO | [ Complete ] dest=/tmp/tmpx5q83vtf/weights size=\"462 MB\" total_elapsed=1.295s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.34s\nLoaded LoRAs in 15.04s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.05s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.14s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.14s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.14s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]", "metrics": { "predict_time": 48.313624146, "total_time": 48.325309 }, "output": [ "https://replicate.delivery/yhqm/7qzR35ZmScJGH9vif68mP1rPjwI2wKmCJXhpIwT46ykaQtvJA/out-0.webp", "https://replicate.delivery/yhqm/ey3IyzbZHXzaE6BOOxmD2b7xEoSyejfi0g85dAAlsk7rB1eNB/out-1.webp", "https://replicate.delivery/yhqm/eYEbdXmmna0hfUrq0e3frEmWu2zXHQKrZdJ5ek7tszMuGU7bC/out-2.webp", "https://replicate.delivery/yhqm/OafFpsVKQwze3EGekyFLAdrfAS0Imje1uzfmGUOYc1emaQtvJA/out-3.webp" ], "started_at": "2024-09-22T10:48:37.149685Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/427z880429rm00cj35crrv5xz0", "cancel": "https://api.replicate.com/v1/predictions/427z880429rm00cj35crrv5xz0/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 42227 Prompt: a gray day with mt fuji in the distance, polaroid photo style [!] txt2img mode Using dev model free=7969735966720 Downloading weights 2024-09-22T10:48:37Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpx5q83vtf/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:48:38Z | INFO | [ Complete ] dest=/tmp/tmpx5q83vtf/weights size="462 MB" total_elapsed=1.295s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.34s Loaded LoRAs in 15.04s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.05s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.11s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:19<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.14s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.14s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.14s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID7tr7xc3j81rm60cj35d8v1521cStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the "Autodesk" and "V-Ray" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \\"Autodesk\\" and \\"V-Ray\\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:50:58.320442Z", "created_at": "2024-09-22T10:50:10.880000Z", "data_removed": false, "error": null, "id": "7tr7xc3j81rm60cj35d8v1521c", "input": { "model": "dev", "prompt": "A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 35946\nPrompt: A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the \"Autodesk\" and \"V-Ray\" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 14.68s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.11s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.02it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.04s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it]\n 18%|█▊ | 5/28 [00:05<00:24, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.10s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it]\n 36%|███▌ | 10/28 [00:10<00:19, 1.11s/it]\n 39%|███▉ | 11/28 [00:12<00:18, 1.11s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.11s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.11s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.11s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.11s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.11s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.11s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.11s/it]\n 68%|██████▊ | 19/28 [00:20<00:10, 1.11s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.11s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.11s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.11s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.11s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:29<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:30<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:30<00:00, 1.11s/it]", "metrics": { "predict_time": 47.429231339, "total_time": 47.440442 }, "output": [ "https://replicate.delivery/yhqm/bhjgbh3WF27aB5VmsbdzlCWbTxabLegqXlFGCOGRd6yIRtvJA/out-0.webp", "https://replicate.delivery/yhqm/ATnFkvC8ctqsL5xwk4YMeSTcbvINuLj7l4nIHFVMF8MJRtvJA/out-1.webp", "https://replicate.delivery/yhqm/8ggytaugURILAJNmdvCuxJjAukcZRyEM5Odp1uXpsffSiafmA/out-2.webp", "https://replicate.delivery/yhqm/evUfLXGGRDvoQUmVeUZ0tsWshrWxhib3N4ZYWkeF1zVIJq9NB/out-3.webp" ], "started_at": "2024-09-22T10:50:10.891210Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7tr7xc3j81rm60cj35d8v1521c", "cancel": "https://api.replicate.com/v1/predictions/7tr7xc3j81rm60cj35d8v1521c/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 35946 Prompt: A charismatic speaker is captured mid-speech. He has long, slightly wavy blonde hair tied back in a ponytail. His expressive face, adorned with a salt-and-pepper beard and mustache, is animated as he gestures with his left hand, displaying a large ring on his pinky finger. He is holding a black microphone in his right hand, speaking passionately. The man is wearing a dark, textured shirt with unique, slightly shimmering patterns, and a green lanyard with multiple badges and logos hanging around his neck. The lanyard features the "Autodesk" and "V-Ray" logos prominently. Behind him, there is a blurred background with a white banner containing logos and text, indicating a professional or conference setting. The overall scene is vibrant and dynamic, capturing the energy of a live presentation., polaroid photo style [!] txt2img mode Using dev model Loaded LoRAs in 14.68s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.11s/it] 7%|▋ | 2/28 [00:02<00:25, 1.02it/s] 11%|█ | 3/28 [00:03<00:26, 1.04s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it] 18%|█▊ | 5/28 [00:05<00:24, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.10s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it] 36%|███▌ | 10/28 [00:10<00:19, 1.11s/it] 39%|███▉ | 11/28 [00:12<00:18, 1.11s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.11s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.11s/it] 50%|█████ | 14/28 [00:15<00:15, 1.11s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.11s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.11s/it] 61%|██████ | 17/28 [00:18<00:12, 1.11s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.11s/it] 68%|██████▊ | 19/28 [00:20<00:10, 1.11s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.11s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.11s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.11s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.11s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:29<00:01, 1.12s/it] 100%|██████████| 28/28 [00:30<00:00, 1.12s/it] 100%|██████████| 28/28 [00:30<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID5et44p0jf9rm40cj35ebdhvs0wStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:52:44.813331Z", "created_at": "2024-09-22T10:51:57.434000Z", "data_removed": false, "error": null, "id": "5et44p0jf9rm40cj35ebdhvs0w", "input": { "model": "dev", "prompt": "handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 5826\nPrompt: handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 14.14s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.01it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.06s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.14s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.14s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.14s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.14s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.14s/it]\n 86%|████████▌ | 24/28 [00:27<00:04, 1.14s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]", "metrics": { "predict_time": 47.369633783, "total_time": 47.379331 }, "output": [ "https://replicate.delivery/yhqm/Q8eUCF9quW07GKDIrCIpLf4pTmjlZf0DFwfIaQTqwuqwPq9NB/out-0.webp", "https://replicate.delivery/yhqm/B6je6FS4MOVPe0iLkFelyVCBitL4E5iusbakKXIOZWfxPq9NB/out-1.webp", "https://replicate.delivery/yhqm/iJnybtLOm2Y3MxXo6h199ugKZeNIEdbPeBLsSAi3Bdr8jafmA/out-2.webp", "https://replicate.delivery/yhqm/i63UmKCCU9ZoDx3hpfQ1kCirZa5pKMEAz5oeg7j8PZr8jafmA/out-3.webp" ], "started_at": "2024-09-22T10:51:57.443698Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5et44p0jf9rm40cj35ebdhvs0w", "cancel": "https://api.replicate.com/v1/predictions/5et44p0jf9rm40cj35ebdhvs0w/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 5826 Prompt: handsome girl in a suit covered with bold tattoos and holding a pistol, polaroid photo style [!] txt2img mode Using dev model Loaded LoRAs in 14.14s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.01it/s] 11%|█ | 3/28 [00:03<00:26, 1.06s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.14s/it] 61%|██████ | 17/28 [00:19<00:12, 1.14s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.14s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.14s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.14s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.14s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.14s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.14s/it] 86%|████████▌ | 24/28 [00:27<00:04, 1.14s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDskz2hp23dxrm60cj35esk8wh18StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a celestial being, polaroid photo style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a celestial being, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a celestial being, polaroid photo style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a celestial being, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a celestial being, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:54:04.451941Z", "created_at": "2024-09-22T10:53:15.503000Z", "data_removed": false, "error": null, "id": "skz2hp23dxrm60cj35esk8wh18", "input": { "model": "dev", "prompt": "a celestial being, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 1637\nPrompt: a celestial being, polaroid photo style\n[!] txt2img mode\nUsing dev model\nfree=9174883975168\nDownloading weights\n2024-09-22T10:53:15Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzzslcmws/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:53:17Z | INFO | [ Complete ] dest=/tmp/tmpzzslcmws/weights size=\"462 MB\" total_elapsed=1.658s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.70s\nLoaded LoRAs in 15.96s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.11s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.02it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.04s/it]\n 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.10s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it]\n 36%|███▌ | 10/28 [00:10<00:20, 1.11s/it]\n 39%|███▉ | 11/28 [00:12<00:18, 1.11s/it]\n 43%|████▎ | 12/28 [00:13<00:17, 1.11s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.11s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.12s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it]\n 61%|██████ | 17/28 [00:18<00:12, 1.12s/it]\n 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it]\n 68%|██████▊ | 19/28 [00:20<00:10, 1.12s/it]\n 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it]\n 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it]\n 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it]\n 96%|█████████▋| 27/28 [00:29<00:01, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.12s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.11s/it]", "metrics": { "predict_time": 48.682993905000004, "total_time": 48.948941 }, "output": [ "https://replicate.delivery/yhqm/5ENpdiGvWRYlJdFdGTsVYtNgKb30DEJRVIuSQ2HepPPmStvJA/out-0.webp", "https://replicate.delivery/yhqm/mkf0kglmg7RUfUFvyqgWizvVlT2CklqerCUAfsqOpyGzUq9NB/out-1.webp", "https://replicate.delivery/yhqm/7rqnB8BhbOqfGaDeXtNHPMqT6JUBY44eX4PVgUVCiOzYK1eNB/out-2.webp", "https://replicate.delivery/yhqm/TahHzrOBLGo9PVrGiJ2Lgm3od3vFsVxw6f4uZqF9zLdmStvJA/out-3.webp" ], "started_at": "2024-09-22T10:53:15.768947Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/skz2hp23dxrm60cj35esk8wh18", "cancel": "https://api.replicate.com/v1/predictions/skz2hp23dxrm60cj35esk8wh18/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 1637 Prompt: a celestial being, polaroid photo style [!] txt2img mode Using dev model free=9174883975168 Downloading weights 2024-09-22T10:53:15Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpzzslcmws/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:53:17Z | INFO | [ Complete ] dest=/tmp/tmpzzslcmws/weights size="462 MB" total_elapsed=1.658s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.70s Loaded LoRAs in 15.96s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.11s/it] 7%|▋ | 2/28 [00:02<00:25, 1.02it/s] 11%|█ | 3/28 [00:03<00:26, 1.04s/it] 14%|█▍ | 4/28 [00:04<00:25, 1.07s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.09s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.10s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.10s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.11s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.11s/it] 36%|███▌ | 10/28 [00:10<00:20, 1.11s/it] 39%|███▉ | 11/28 [00:12<00:18, 1.11s/it] 43%|████▎ | 12/28 [00:13<00:17, 1.11s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.11s/it] 50%|█████ | 14/28 [00:15<00:15, 1.12s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.12s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.12s/it] 61%|██████ | 17/28 [00:18<00:12, 1.12s/it] 64%|██████▍ | 18/28 [00:19<00:11, 1.12s/it] 68%|██████▊ | 19/28 [00:20<00:10, 1.12s/it] 71%|███████▏ | 20/28 [00:22<00:08, 1.12s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.12s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.12s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.12s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.12s/it] 89%|████████▉ | 25/28 [00:27<00:03, 1.12s/it] 93%|█████████▎| 26/28 [00:28<00:02, 1.12s/it] 96%|█████████▋| 27/28 [00:29<00:01, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.12s/it] 100%|██████████| 28/28 [00:31<00:00, 1.11s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badID525ecg9v8srm00cj35fr51a410StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a japanese woman with a bit smile, polaroid photo style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a japanese woman with a bit smile, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a japanese woman with a bit smile, polaroid photo style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a japanese woman with a bit smile, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a japanese woman with a bit smile, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:57:01.862093Z", "created_at": "2024-09-22T10:55:24.486000Z", "data_removed": false, "error": null, "id": "525ecg9v8srm00cj35fr51a410", "input": { "model": "dev", "prompt": "a japanese woman with a bit smile, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 21603\nPrompt: a japanese woman with a bit smile, polaroid photo style\n[!] txt2img mode\nUsing dev model\nfree=6629757927424\nDownloading weights\n2024-09-22T10:56:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpxz037jzi/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:56:14Z | INFO | [ Complete ] dest=/tmp/tmpxz037jzi/weights size=\"462 MB\" total_elapsed=1.510s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.56s\nLoaded LoRAs in 15.74s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.14s/it]\n 7%|▋ | 2/28 [00:02<00:26, 1.00s/it]\n 11%|█ | 3/28 [00:03<00:26, 1.07s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.10s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.11s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.13s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.13s/it]\n 32%|███▏ | 9/28 [00:10<00:21, 1.14s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.14s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.14s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.14s/it]\n 46%|████▋ | 13/28 [00:14<00:17, 1.14s/it]\n 50%|█████ | 14/28 [00:15<00:16, 1.14s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.14s/it]\n 57%|█████▋ | 16/28 [00:18<00:13, 1.15s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.15s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.15s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.15s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.15s/it]\n 75%|███████▌ | 21/28 [00:23<00:08, 1.15s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.15s/it]\n 82%|████████▏ | 23/28 [00:26<00:05, 1.15s/it]\n 86%|████████▌ | 24/28 [00:27<00:04, 1.15s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.15s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.15s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.15s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.15s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]", "metrics": { "predict_time": 49.197467289, "total_time": 97.376093 }, "output": [ "https://replicate.delivery/yhqm/I84TWVtmNhpSKJmLidjkTNhXSfuJzNoM4xL0HT6MfUy9nafmA/out-0.webp", "https://replicate.delivery/yhqm/2ZddT0LeGX2UByH1Im9JwjDBmtZht8tUoIMq1rOGGj2enafmA/out-1.webp", "https://replicate.delivery/yhqm/MAoUedU3kARrOSCVqoRzEHYaQXtg9oDAXmJus5fBoHI9nafmA/out-2.webp", "https://replicate.delivery/yhqm/IvldBrDLe3UaK65jXKfxlSxzfYuuA0LPzLxlvVf2cvftfp23E/out-3.webp" ], "started_at": "2024-09-22T10:56:12.664626Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/525ecg9v8srm00cj35fr51a410", "cancel": "https://api.replicate.com/v1/predictions/525ecg9v8srm00cj35fr51a410/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 21603 Prompt: a japanese woman with a bit smile, polaroid photo style [!] txt2img mode Using dev model free=6629757927424 Downloading weights 2024-09-22T10:56:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpxz037jzi/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:56:14Z | INFO | [ Complete ] dest=/tmp/tmpxz037jzi/weights size="462 MB" total_elapsed=1.510s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.56s Loaded LoRAs in 15.74s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.14s/it] 7%|▋ | 2/28 [00:02<00:26, 1.00s/it] 11%|█ | 3/28 [00:03<00:26, 1.07s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.10s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.11s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.13s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.13s/it] 32%|███▏ | 9/28 [00:10<00:21, 1.14s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.14s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.14s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.14s/it] 46%|████▋ | 13/28 [00:14<00:17, 1.14s/it] 50%|█████ | 14/28 [00:15<00:16, 1.14s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.14s/it] 57%|█████▋ | 16/28 [00:18<00:13, 1.15s/it] 61%|██████ | 17/28 [00:19<00:12, 1.15s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.15s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.15s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.15s/it] 75%|███████▌ | 21/28 [00:23<00:08, 1.15s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.15s/it] 82%|████████▏ | 23/28 [00:26<00:05, 1.15s/it] 86%|████████▌ | 24/28 [00:27<00:04, 1.15s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.15s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.15s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.15s/it] 100%|██████████| 28/28 [00:31<00:00, 1.15s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it]Prediction
aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51badIDebyhhhjfwhrm40cj35gv0ezr78StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style
- lora_scale
- 1
- num_outputs
- 4
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", { input: { model: "dev", prompt: "a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style", lora_scale: 1, num_outputs: 4, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", input={ "model": "dev", "prompt": "a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run aramintak/pola-style using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "aramintak/pola-style:67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad", "input": { "model": "dev", "prompt": "a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-22T10:58:37.917732Z", "created_at": "2024-09-22T10:57:40.836000Z", "data_removed": false, "error": null, "id": "ebyhhhjfwhrm40cj35gv0ezr78", "input": { "model": "dev", "prompt": "a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style", "lora_scale": 1, "num_outputs": 4, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 27709\nPrompt: a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style\n[!] txt2img mode\nUsing dev model\nfree=7362761596928\nDownloading weights\n2024-09-22T10:57:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpqsw731tc/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\n2024-09-22T10:57:51Z | INFO | [ Complete ] dest=/tmp/tmpqsw731tc/weights size=\"462 MB\" total_elapsed=1.371s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar\nDownloaded weights in 1.42s\nLoaded LoRAs in 14.41s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:30, 1.13s/it]\n 7%|▋ | 2/28 [00:02<00:25, 1.00it/s]\n 11%|█ | 3/28 [00:03<00:26, 1.06s/it]\n 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it]\n 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it]\n 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it]\n 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it]\n 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it]\n 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it]\n 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it]\n 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it]\n 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it]\n 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it]\n 50%|█████ | 14/28 [00:15<00:15, 1.13s/it]\n 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it]\n 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it]\n 61%|██████ | 17/28 [00:19<00:12, 1.13s/it]\n 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it]\n 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it]\n 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it]\n 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it]\n 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it]\n 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it]\n 86%|████████▌ | 24/28 [00:26<00:04, 1.14s/it]\n 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it]\n 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it]\n 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.14s/it]\n100%|██████████| 28/28 [00:31<00:00, 1.13s/it]", "metrics": { "predict_time": 47.711600641, "total_time": 57.081732 }, "output": [ "https://replicate.delivery/yhqm/Beyffmwf1RYqESIS8Pfa8MUNtqtgIwznXEwle2iqNwTZXq23E/out-0.webp", "https://replicate.delivery/yhqm/pTdSZrWZtKpPLVFMgBTurkwIOMhclxqZYsflmSvuQM1uUtvJA/out-1.webp", "https://replicate.delivery/yhqm/1ij5hyMTBGZ4DJLffiutqJeuZCfvCVyzBZguTPylMrg0lq9NB/out-2.webp", "https://replicate.delivery/yhqm/FGqmkjHQkSpxFpQcHUH1zsNfz3caGrSEb3XFXsDbHGhuUtvJA/out-3.webp" ], "started_at": "2024-09-22T10:57:50.206131Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ebyhhhjfwhrm40cj35gv0ezr78", "cancel": "https://api.replicate.com/v1/predictions/ebyhhhjfwhrm40cj35gv0ezr78/cancel" }, "version": "67c27855ad0334cbca0f35cd5192777d885d5351e1d3e7149fe208d88db51bad" }Generated inUsing seed: 27709 Prompt: a messy desk with an pile of old cassette tapes from different indie bands with scrawled labels on them, still life, polaroid photo style [!] txt2img mode Using dev model free=7362761596928 Downloading weights 2024-09-22T10:57:50Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpqsw731tc/weights url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar 2024-09-22T10:57:51Z | INFO | [ Complete ] dest=/tmp/tmpqsw731tc/weights size="462 MB" total_elapsed=1.371s url=https://replicate.delivery/yhqm/dY5GE1khNN7pCh4DOAzarVjQmigSzx4Ql5yBOMwP7BlYE03E/trained_model.tar Downloaded weights in 1.42s Loaded LoRAs in 14.41s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:30, 1.13s/it] 7%|▋ | 2/28 [00:02<00:25, 1.00it/s] 11%|█ | 3/28 [00:03<00:26, 1.06s/it] 14%|█▍ | 4/28 [00:04<00:26, 1.09s/it] 18%|█▊ | 5/28 [00:05<00:25, 1.10s/it] 21%|██▏ | 6/28 [00:06<00:24, 1.12s/it] 25%|██▌ | 7/28 [00:07<00:23, 1.12s/it] 29%|██▊ | 8/28 [00:08<00:22, 1.12s/it] 32%|███▏ | 9/28 [00:09<00:21, 1.13s/it] 36%|███▌ | 10/28 [00:11<00:20, 1.13s/it] 39%|███▉ | 11/28 [00:12<00:19, 1.13s/it] 43%|████▎ | 12/28 [00:13<00:18, 1.13s/it] 46%|████▋ | 13/28 [00:14<00:16, 1.13s/it] 50%|█████ | 14/28 [00:15<00:15, 1.13s/it] 54%|█████▎ | 15/28 [00:16<00:14, 1.13s/it] 57%|█████▋ | 16/28 [00:17<00:13, 1.13s/it] 61%|██████ | 17/28 [00:19<00:12, 1.13s/it] 64%|██████▍ | 18/28 [00:20<00:11, 1.13s/it] 68%|██████▊ | 19/28 [00:21<00:10, 1.13s/it] 71%|███████▏ | 20/28 [00:22<00:09, 1.13s/it] 75%|███████▌ | 21/28 [00:23<00:07, 1.13s/it] 79%|███████▊ | 22/28 [00:24<00:06, 1.13s/it] 82%|████████▏ | 23/28 [00:25<00:05, 1.13s/it] 86%|████████▌ | 24/28 [00:26<00:04, 1.14s/it] 89%|████████▉ | 25/28 [00:28<00:03, 1.14s/it] 93%|█████████▎| 26/28 [00:29<00:02, 1.14s/it] 96%|█████████▋| 27/28 [00:30<00:01, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.14s/it] 100%|██████████| 28/28 [00:31<00:00, 1.13s/it]
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