grassyguru
/
archslra
- Public
- 48 runs
-
H100
Prediction
grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3IDeehbj6dkfxrm60chjtybvv0n28StatusSucceededSourceWebHardwareH100Total durationCreatedby @grassyguruInput
- model
- dev
- prompt
- ARCHSLRA knight in armor sailing in boat
- lora_scale
- 0.87
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 1
- num_inference_steps
- 34
{ "model": "dev", "prompt": "ARCHSLRA knight in armor sailing in boat", "lora_scale": 0.87, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", { input: { model: "dev", prompt: "ARCHSLRA knight in armor sailing in boat", lora_scale: 0.87, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 1, num_inference_steps: 34 } } ); // 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 grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", input={ "model": "dev", "prompt": "ARCHSLRA knight in armor sailing in boat", "lora_scale": 0.87, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run grassyguru/archslra 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": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", "input": { "model": "dev", "prompt": "ARCHSLRA knight in armor sailing in boat", "lora_scale": 0.87, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T02:07:37.459291Z", "created_at": "2024-08-28T02:07:14.815000Z", "data_removed": false, "error": null, "id": "eehbj6dkfxrm60chjtybvv0n28", "input": { "model": "dev", "prompt": "ARCHSLRA knight in armor sailing in boat", "lora_scale": 0.87, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }, "logs": "Using seed: 65486\nPrompt: ARCHSLRA knight in armor sailing in boat\ntxt2img mode\nUsing dev model\nfree=9793144258560\nDownloading weights\n2024-08-28T02:07:14Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9ozgw91w/weights url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar\n2024-08-28T02:07:19Z | INFO | [ Complete ] dest=/tmp/tmp9ozgw91w/weights size=\"172 MB\" total_elapsed=4.719s url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar\nDownloaded weights in 4.75s\nLoaded LoRAs in 12.64s\n 0%| | 0/34 [00:00<?, ?it/s]\n 3%|▎ | 1/34 [00:00<00:09, 3.56it/s]\n 6%|▌ | 2/34 [00:00<00:07, 4.00it/s]\n 9%|▉ | 3/34 [00:00<00:08, 3.80it/s]\n 12%|█▏ | 4/34 [00:01<00:08, 3.70it/s]\n 15%|█▍ | 5/34 [00:01<00:07, 3.65it/s]\n 18%|█▊ | 6/34 [00:01<00:07, 3.62it/s]\n 21%|██ | 7/34 [00:01<00:07, 3.61it/s]\n 24%|██▎ | 8/34 [00:02<00:07, 3.60it/s]\n 26%|██▋ | 9/34 [00:02<00:06, 3.59it/s]\n 29%|██▉ | 10/34 [00:02<00:06, 3.59it/s]\n 32%|███▏ | 11/34 [00:03<00:06, 3.59it/s]\n 35%|███▌ | 12/34 [00:03<00:06, 3.58it/s]\n 38%|███▊ | 13/34 [00:03<00:05, 3.58it/s]\n 41%|████ | 14/34 [00:03<00:05, 3.58it/s]\n 44%|████▍ | 15/34 [00:04<00:05, 3.58it/s]\n 47%|████▋ | 16/34 [00:04<00:05, 3.58it/s]\n 50%|█████ | 17/34 [00:04<00:04, 3.57it/s]\n 53%|█████▎ | 18/34 [00:04<00:04, 3.58it/s]\n 56%|█████▌ | 19/34 [00:05<00:04, 3.58it/s]\n 59%|█████▉ | 20/34 [00:05<00:03, 3.57it/s]\n 62%|██████▏ | 21/34 [00:05<00:03, 3.57it/s]\n 65%|██████▍ | 22/34 [00:06<00:03, 3.58it/s]\n 68%|██████▊ | 23/34 [00:06<00:03, 3.58it/s]\n 71%|███████ | 24/34 [00:06<00:02, 3.58it/s]\n 74%|███████▎ | 25/34 [00:06<00:02, 3.57it/s]\n 76%|███████▋ | 26/34 [00:07<00:02, 3.58it/s]\n 79%|███████▉ | 27/34 [00:07<00:01, 3.58it/s]\n 82%|████████▏ | 28/34 [00:07<00:01, 3.57it/s]\n 85%|████████▌ | 29/34 [00:08<00:01, 3.57it/s]\n 88%|████████▊ | 30/34 [00:08<00:01, 3.57it/s]\n 91%|█████████ | 31/34 [00:08<00:00, 3.58it/s]\n 94%|█████████▍| 32/34 [00:08<00:00, 3.58it/s]\n 97%|█████████▋| 33/34 [00:09<00:00, 3.57it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.58it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.59it/s]", "metrics": { "predict_time": 22.635936269, "total_time": 22.644291 }, "output": [ "https://replicate.delivery/yhqm/aTNvbsfLNr13ekGL4HdgQ4gY01ATeQAqAeVfvVfz4DAda4w1E/out-0.webp" ], "started_at": "2024-08-28T02:07:14.823355Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/eehbj6dkfxrm60chjtybvv0n28", "cancel": "https://api.replicate.com/v1/predictions/eehbj6dkfxrm60chjtybvv0n28/cancel" }, "version": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3" }Generated inUsing seed: 65486 Prompt: ARCHSLRA knight in armor sailing in boat txt2img mode Using dev model free=9793144258560 Downloading weights 2024-08-28T02:07:14Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9ozgw91w/weights url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar 2024-08-28T02:07:19Z | INFO | [ Complete ] dest=/tmp/tmp9ozgw91w/weights size="172 MB" total_elapsed=4.719s url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar Downloaded weights in 4.75s Loaded LoRAs in 12.64s 0%| | 0/34 [00:00<?, ?it/s] 3%|▎ | 1/34 [00:00<00:09, 3.56it/s] 6%|▌ | 2/34 [00:00<00:07, 4.00it/s] 9%|▉ | 3/34 [00:00<00:08, 3.80it/s] 12%|█▏ | 4/34 [00:01<00:08, 3.70it/s] 15%|█▍ | 5/34 [00:01<00:07, 3.65it/s] 18%|█▊ | 6/34 [00:01<00:07, 3.62it/s] 21%|██ | 7/34 [00:01<00:07, 3.61it/s] 24%|██▎ | 8/34 [00:02<00:07, 3.60it/s] 26%|██▋ | 9/34 [00:02<00:06, 3.59it/s] 29%|██▉ | 10/34 [00:02<00:06, 3.59it/s] 32%|███▏ | 11/34 [00:03<00:06, 3.59it/s] 35%|███▌ | 12/34 [00:03<00:06, 3.58it/s] 38%|███▊ | 13/34 [00:03<00:05, 3.58it/s] 41%|████ | 14/34 [00:03<00:05, 3.58it/s] 44%|████▍ | 15/34 [00:04<00:05, 3.58it/s] 47%|████▋ | 16/34 [00:04<00:05, 3.58it/s] 50%|█████ | 17/34 [00:04<00:04, 3.57it/s] 53%|█████▎ | 18/34 [00:04<00:04, 3.58it/s] 56%|█████▌ | 19/34 [00:05<00:04, 3.58it/s] 59%|█████▉ | 20/34 [00:05<00:03, 3.57it/s] 62%|██████▏ | 21/34 [00:05<00:03, 3.57it/s] 65%|██████▍ | 22/34 [00:06<00:03, 3.58it/s] 68%|██████▊ | 23/34 [00:06<00:03, 3.58it/s] 71%|███████ | 24/34 [00:06<00:02, 3.58it/s] 74%|███████▎ | 25/34 [00:06<00:02, 3.57it/s] 76%|███████▋ | 26/34 [00:07<00:02, 3.58it/s] 79%|███████▉ | 27/34 [00:07<00:01, 3.58it/s] 82%|████████▏ | 28/34 [00:07<00:01, 3.57it/s] 85%|████████▌ | 29/34 [00:08<00:01, 3.57it/s] 88%|████████▊ | 30/34 [00:08<00:01, 3.57it/s] 91%|█████████ | 31/34 [00:08<00:00, 3.58it/s] 94%|█████████▍| 32/34 [00:08<00:00, 3.58it/s] 97%|█████████▋| 33/34 [00:09<00:00, 3.57it/s] 100%|██████████| 34/34 [00:09<00:00, 3.58it/s] 100%|██████████| 34/34 [00:09<00:00, 3.59it/s]Prediction
grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3ID9bvd8xqs35rm20chjv2rjxpmjwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.
- lora_scale
- 2
- num_outputs
- 1
- aspect_ratio
- 9:16
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 1
- num_inference_steps
- 34
{ "model": "dev", "prompt": "ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", { input: { model: "dev", prompt: "ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.", lora_scale: 2, num_outputs: 1, aspect_ratio: "9:16", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 1, num_inference_steps: 34 } } ); // 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 grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", input={ "model": "dev", "prompt": "ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run grassyguru/archslra 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": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", "input": { "model": "dev", "prompt": "ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T02:17:45.472783Z", "created_at": "2024-08-28T02:17:22.457000Z", "data_removed": false, "error": null, "id": "9bvd8xqs35rm20chjv2rjxpmjw", "input": { "model": "dev", "prompt": "ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "9:16", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }, "logs": "Using seed: 52649\nPrompt: ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style.\ntxt2img mode\nUsing dev model\nfree=9711338754048\nDownloading weights\n2024-08-28T02:17:22Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv0lqi1c_/weights url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar\n2024-08-28T02:17:26Z | INFO | [ Complete ] dest=/tmp/tmpv0lqi1c_/weights size=\"172 MB\" total_elapsed=4.042s url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar\nDownloaded weights in 4.07s\nLoaded LoRAs in 12.95s\n 0%| | 0/34 [00:00<?, ?it/s]\n 3%|▎ | 1/34 [00:00<00:09, 3.56it/s]\n 6%|▌ | 2/34 [00:00<00:08, 3.98it/s]\n 9%|▉ | 3/34 [00:00<00:08, 3.78it/s]\n 12%|█▏ | 4/34 [00:01<00:08, 3.68it/s]\n 15%|█▍ | 5/34 [00:01<00:07, 3.63it/s]\n 18%|█▊ | 6/34 [00:01<00:07, 3.60it/s]\n 21%|██ | 7/34 [00:01<00:07, 3.58it/s]\n 24%|██▎ | 8/34 [00:02<00:07, 3.57it/s]\n 26%|██▋ | 9/34 [00:02<00:07, 3.56it/s]\n 29%|██▉ | 10/34 [00:02<00:06, 3.56it/s]\n 32%|███▏ | 11/34 [00:03<00:06, 3.55it/s]\n 35%|███▌ | 12/34 [00:03<00:06, 3.55it/s]\n 38%|███▊ | 13/34 [00:03<00:05, 3.55it/s]\n 41%|████ | 14/34 [00:03<00:05, 3.56it/s]\n 44%|████▍ | 15/34 [00:04<00:05, 3.56it/s]\n 47%|████▋ | 16/34 [00:04<00:05, 3.56it/s]\n 50%|█████ | 17/34 [00:04<00:04, 3.56it/s]\n 53%|█████▎ | 18/34 [00:05<00:04, 3.56it/s]\n 56%|█████▌ | 19/34 [00:05<00:04, 3.55it/s]\n 59%|█████▉ | 20/34 [00:05<00:03, 3.56it/s]\n 62%|██████▏ | 21/34 [00:05<00:03, 3.54it/s]\n 65%|██████▍ | 22/34 [00:06<00:03, 3.54it/s]\n 68%|██████▊ | 23/34 [00:06<00:03, 3.54it/s]\n 71%|███████ | 24/34 [00:06<00:02, 3.55it/s]\n 74%|███████▎ | 25/34 [00:06<00:02, 3.55it/s]\n 76%|███████▋ | 26/34 [00:07<00:02, 3.55it/s]\n 79%|███████▉ | 27/34 [00:07<00:01, 3.56it/s]\n 82%|████████▏ | 28/34 [00:07<00:01, 3.55it/s]\n 85%|████████▌ | 29/34 [00:08<00:01, 3.56it/s]\n 88%|████████▊ | 30/34 [00:08<00:01, 3.54it/s]\n 91%|█████████ | 31/34 [00:08<00:00, 3.55it/s]\n 94%|█████████▍| 32/34 [00:08<00:00, 3.55it/s]\n 97%|█████████▋| 33/34 [00:09<00:00, 3.55it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.55it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.57it/s]", "metrics": { "predict_time": 23.00996637, "total_time": 23.015783 }, "output": [ "https://replicate.delivery/yhqm/17mdCfZ8NFwvWa1G7JO7nyuyix3f9cDwybiNFN4lplhJrDXTA/out-0.webp" ], "started_at": "2024-08-28T02:17:22.462816Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/9bvd8xqs35rm20chjv2rjxpmjw", "cancel": "https://api.replicate.com/v1/predictions/9bvd8xqs35rm20chjv2rjxpmjw/cancel" }, "version": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3" }Generated inUsing seed: 52649 Prompt: ARCHSLRA of a boat with a group of people on it, sailing in the ocean. The boat is white and has a sail. The people on the boat are wearing white clothes and hats. The scene is set at night with the stars shining brightly in the sky. The painting has a whimsical and playful style. txt2img mode Using dev model free=9711338754048 Downloading weights 2024-08-28T02:17:22Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpv0lqi1c_/weights url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar 2024-08-28T02:17:26Z | INFO | [ Complete ] dest=/tmp/tmpv0lqi1c_/weights size="172 MB" total_elapsed=4.042s url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar Downloaded weights in 4.07s Loaded LoRAs in 12.95s 0%| | 0/34 [00:00<?, ?it/s] 3%|▎ | 1/34 [00:00<00:09, 3.56it/s] 6%|▌ | 2/34 [00:00<00:08, 3.98it/s] 9%|▉ | 3/34 [00:00<00:08, 3.78it/s] 12%|█▏ | 4/34 [00:01<00:08, 3.68it/s] 15%|█▍ | 5/34 [00:01<00:07, 3.63it/s] 18%|█▊ | 6/34 [00:01<00:07, 3.60it/s] 21%|██ | 7/34 [00:01<00:07, 3.58it/s] 24%|██▎ | 8/34 [00:02<00:07, 3.57it/s] 26%|██▋ | 9/34 [00:02<00:07, 3.56it/s] 29%|██▉ | 10/34 [00:02<00:06, 3.56it/s] 32%|███▏ | 11/34 [00:03<00:06, 3.55it/s] 35%|███▌ | 12/34 [00:03<00:06, 3.55it/s] 38%|███▊ | 13/34 [00:03<00:05, 3.55it/s] 41%|████ | 14/34 [00:03<00:05, 3.56it/s] 44%|████▍ | 15/34 [00:04<00:05, 3.56it/s] 47%|████▋ | 16/34 [00:04<00:05, 3.56it/s] 50%|█████ | 17/34 [00:04<00:04, 3.56it/s] 53%|█████▎ | 18/34 [00:05<00:04, 3.56it/s] 56%|█████▌ | 19/34 [00:05<00:04, 3.55it/s] 59%|█████▉ | 20/34 [00:05<00:03, 3.56it/s] 62%|██████▏ | 21/34 [00:05<00:03, 3.54it/s] 65%|██████▍ | 22/34 [00:06<00:03, 3.54it/s] 68%|██████▊ | 23/34 [00:06<00:03, 3.54it/s] 71%|███████ | 24/34 [00:06<00:02, 3.55it/s] 74%|███████▎ | 25/34 [00:06<00:02, 3.55it/s] 76%|███████▋ | 26/34 [00:07<00:02, 3.55it/s] 79%|███████▉ | 27/34 [00:07<00:01, 3.56it/s] 82%|████████▏ | 28/34 [00:07<00:01, 3.55it/s] 85%|████████▌ | 29/34 [00:08<00:01, 3.56it/s] 88%|████████▊ | 30/34 [00:08<00:01, 3.54it/s] 91%|█████████ | 31/34 [00:08<00:00, 3.55it/s] 94%|█████████▍| 32/34 [00:08<00:00, 3.55it/s] 97%|█████████▋| 33/34 [00:09<00:00, 3.55it/s] 100%|██████████| 34/34 [00:09<00:00, 3.55it/s] 100%|██████████| 34/34 [00:09<00:00, 3.57it/s]Prediction
grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3IDq0kjr19aw5rm20chkana06f5vwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night
- lora_scale
- 2
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 1
- num_inference_steps
- 34
{ "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", { input: { model: "dev", prompt: "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", lora_scale: 2, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 1, num_inference_steps: 34 } } ); // 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 grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", input={ "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run grassyguru/archslra 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": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", "input": { "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T20:25:53.223095Z", "created_at": "2024-08-28T20:25:29.057000Z", "data_removed": false, "error": null, "id": "q0kjr19aw5rm20chkana06f5vw", "input": { "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 2, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }, "logs": "Using seed: 33592\nPrompt: ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night\ntxt2img mode\nUsing dev model\nLoaded LoRAs in 9.30s\n 0%| | 0/34 [00:00<?, ?it/s]\n 3%|▎ | 1/34 [00:00<00:09, 3.57it/s]\n 6%|▌ | 2/34 [00:00<00:08, 4.00it/s]\n 9%|▉ | 3/34 [00:00<00:08, 3.78it/s]\n 12%|█▏ | 4/34 [00:01<00:08, 3.69it/s]\n 15%|█▍ | 5/34 [00:01<00:07, 3.65it/s]\n 18%|█▊ | 6/34 [00:01<00:07, 3.62it/s]\n 21%|██ | 7/34 [00:01<00:07, 3.60it/s]\n 24%|██▎ | 8/34 [00:02<00:07, 3.59it/s]\n 26%|██▋ | 9/34 [00:02<00:06, 3.59it/s]\n 29%|██▉ | 10/34 [00:02<00:06, 3.58it/s]\n 32%|███▏ | 11/34 [00:03<00:06, 3.58it/s]\n 35%|███▌ | 12/34 [00:03<00:06, 3.57it/s]\n 38%|███▊ | 13/34 [00:03<00:05, 3.57it/s]\n 41%|████ | 14/34 [00:03<00:05, 3.57it/s]\n 44%|████▍ | 15/34 [00:04<00:05, 3.57it/s]\n 47%|████▋ | 16/34 [00:04<00:05, 3.57it/s]\n 50%|█████ | 17/34 [00:04<00:04, 3.57it/s]\n 53%|█████▎ | 18/34 [00:04<00:04, 3.57it/s]\n 56%|█████▌ | 19/34 [00:05<00:04, 3.57it/s]\n 59%|█████▉ | 20/34 [00:05<00:03, 3.57it/s]\n 62%|██████▏ | 21/34 [00:05<00:03, 3.58it/s]\n 65%|██████▍ | 22/34 [00:06<00:03, 3.58it/s]\n 68%|██████▊ | 23/34 [00:06<00:03, 3.58it/s]\n 71%|███████ | 24/34 [00:06<00:02, 3.58it/s]\n 74%|███████▎ | 25/34 [00:06<00:02, 3.57it/s]\n 76%|███████▋ | 26/34 [00:07<00:02, 3.58it/s]\n 79%|███████▉ | 27/34 [00:07<00:01, 3.58it/s]\n 82%|████████▏ | 28/34 [00:07<00:01, 3.58it/s]\n 85%|████████▌ | 29/34 [00:08<00:01, 3.58it/s]\n 88%|████████▊ | 30/34 [00:08<00:01, 3.58it/s]\n 91%|█████████ | 31/34 [00:08<00:00, 3.58it/s]\n 94%|█████████▍| 32/34 [00:08<00:00, 3.58it/s]\n 97%|█████████▋| 33/34 [00:09<00:00, 3.58it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.58it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.59it/s]", "metrics": { "predict_time": 19.314143956, "total_time": 24.166095 }, "output": [ "https://replicate.delivery/yhqm/g2OBcPfF7Z2iDqomQ3BJKubhqIf3fCebnfDVfKreLSfKRnTXTA/out-0.webp" ], "started_at": "2024-08-28T20:25:33.908951Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/q0kjr19aw5rm20chkana06f5vw", "cancel": "https://api.replicate.com/v1/predictions/q0kjr19aw5rm20chkana06f5vw/cancel" }, "version": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3" }Generated inUsing seed: 33592 Prompt: ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night txt2img mode Using dev model Loaded LoRAs in 9.30s 0%| | 0/34 [00:00<?, ?it/s] 3%|▎ | 1/34 [00:00<00:09, 3.57it/s] 6%|▌ | 2/34 [00:00<00:08, 4.00it/s] 9%|▉ | 3/34 [00:00<00:08, 3.78it/s] 12%|█▏ | 4/34 [00:01<00:08, 3.69it/s] 15%|█▍ | 5/34 [00:01<00:07, 3.65it/s] 18%|█▊ | 6/34 [00:01<00:07, 3.62it/s] 21%|██ | 7/34 [00:01<00:07, 3.60it/s] 24%|██▎ | 8/34 [00:02<00:07, 3.59it/s] 26%|██▋ | 9/34 [00:02<00:06, 3.59it/s] 29%|██▉ | 10/34 [00:02<00:06, 3.58it/s] 32%|███▏ | 11/34 [00:03<00:06, 3.58it/s] 35%|███▌ | 12/34 [00:03<00:06, 3.57it/s] 38%|███▊ | 13/34 [00:03<00:05, 3.57it/s] 41%|████ | 14/34 [00:03<00:05, 3.57it/s] 44%|████▍ | 15/34 [00:04<00:05, 3.57it/s] 47%|████▋ | 16/34 [00:04<00:05, 3.57it/s] 50%|█████ | 17/34 [00:04<00:04, 3.57it/s] 53%|█████▎ | 18/34 [00:04<00:04, 3.57it/s] 56%|█████▌ | 19/34 [00:05<00:04, 3.57it/s] 59%|█████▉ | 20/34 [00:05<00:03, 3.57it/s] 62%|██████▏ | 21/34 [00:05<00:03, 3.58it/s] 65%|██████▍ | 22/34 [00:06<00:03, 3.58it/s] 68%|██████▊ | 23/34 [00:06<00:03, 3.58it/s] 71%|███████ | 24/34 [00:06<00:02, 3.58it/s] 74%|███████▎ | 25/34 [00:06<00:02, 3.57it/s] 76%|███████▋ | 26/34 [00:07<00:02, 3.58it/s] 79%|███████▉ | 27/34 [00:07<00:01, 3.58it/s] 82%|████████▏ | 28/34 [00:07<00:01, 3.58it/s] 85%|████████▌ | 29/34 [00:08<00:01, 3.58it/s] 88%|████████▊ | 30/34 [00:08<00:01, 3.58it/s] 91%|█████████ | 31/34 [00:08<00:00, 3.58it/s] 94%|█████████▍| 32/34 [00:08<00:00, 3.58it/s] 97%|█████████▋| 33/34 [00:09<00:00, 3.58it/s] 100%|██████████| 34/34 [00:09<00:00, 3.58it/s] 100%|██████████| 34/34 [00:09<00:00, 3.59it/s]Prediction
grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3IDzaxv8e9p09rm40chkant8n1fdwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 16:9
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- extra_lora_scale
- 1
- num_inference_steps
- 34
{ "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", { input: { model: "dev", prompt: "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", lora_scale: 1, num_outputs: 1, aspect_ratio: "16:9", output_format: "webp", guidance_scale: 3.5, output_quality: 80, extra_lora_scale: 1, num_inference_steps: 34 } } ); // 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 grassyguru/archslra using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "grassyguru/archslra:c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", input={ "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run grassyguru/archslra 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": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3", "input": { "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-28T20:26:58.070059Z", "created_at": "2024-08-28T20:26:37.442000Z", "data_removed": false, "error": null, "id": "zaxv8e9p09rm40chkant8n1fdw", "input": { "model": "dev", "prompt": "ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "16:9", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "extra_lora_scale": 1, "num_inference_steps": 34 }, "logs": "Using seed: 29949\nPrompt: ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night\ntxt2img mode\nUsing dev model\nfree=9093396889600\nDownloading weights\n2024-08-28T20:26:37Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp7uynhdk0/weights url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar\n2024-08-28T20:26:39Z | INFO | [ Complete ] dest=/tmp/tmp7uynhdk0/weights size=\"172 MB\" total_elapsed=1.698s url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar\nDownloaded weights in 1.80s\nLoaded LoRAs in 10.92s\n 0%| | 0/34 [00:00<?, ?it/s]\n 3%|▎ | 1/34 [00:00<00:08, 3.68it/s]\n 6%|▌ | 2/34 [00:00<00:07, 4.24it/s]\n 9%|▉ | 3/34 [00:00<00:07, 3.96it/s]\n 12%|█▏ | 4/34 [00:01<00:07, 3.84it/s]\n 15%|█▍ | 5/34 [00:01<00:07, 3.78it/s]\n 18%|█▊ | 6/34 [00:01<00:07, 3.74it/s]\n 21%|██ | 7/34 [00:01<00:07, 3.72it/s]\n 24%|██▎ | 8/34 [00:02<00:07, 3.71it/s]\n 26%|██▋ | 9/34 [00:02<00:06, 3.70it/s]\n 29%|██▉ | 10/34 [00:02<00:06, 3.69it/s]\n 32%|███▏ | 11/34 [00:02<00:06, 3.69it/s]\n 35%|███▌ | 12/34 [00:03<00:05, 3.69it/s]\n 38%|███▊ | 13/34 [00:03<00:05, 3.69it/s]\n 41%|████ | 14/34 [00:03<00:05, 3.69it/s]\n 44%|████▍ | 15/34 [00:04<00:05, 3.69it/s]\n 47%|████▋ | 16/34 [00:04<00:04, 3.69it/s]\n 50%|█████ | 17/34 [00:04<00:04, 3.69it/s]\n 53%|█████▎ | 18/34 [00:04<00:04, 3.68it/s]\n 56%|█████▌ | 19/34 [00:05<00:04, 3.69it/s]\n 59%|█████▉ | 20/34 [00:05<00:03, 3.69it/s]\n 62%|██████▏ | 21/34 [00:05<00:03, 3.69it/s]\n 65%|██████▍ | 22/34 [00:05<00:03, 3.69it/s]\n 68%|██████▊ | 23/34 [00:06<00:02, 3.69it/s]\n 71%|███████ | 24/34 [00:06<00:02, 3.69it/s]\n 74%|███████▎ | 25/34 [00:06<00:02, 3.69it/s]\n 76%|███████▋ | 26/34 [00:06<00:02, 3.68it/s]\n 79%|███████▉ | 27/34 [00:07<00:01, 3.69it/s]\n 82%|████████▏ | 28/34 [00:07<00:01, 3.69it/s]\n 85%|████████▌ | 29/34 [00:07<00:01, 3.69it/s]\n 88%|████████▊ | 30/34 [00:08<00:01, 3.69it/s]\n 91%|█████████ | 31/34 [00:08<00:00, 3.69it/s]\n 94%|█████████▍| 32/34 [00:08<00:00, 3.69it/s]\n 97%|█████████▋| 33/34 [00:08<00:00, 3.69it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.69it/s]\n100%|██████████| 34/34 [00:09<00:00, 3.71it/s]", "metrics": { "predict_time": 20.61762558, "total_time": 20.628059 }, "output": [ "https://replicate.delivery/yhqm/Sfs7THWmQDyAZKdKxjjAADhg2oinpawqLcnC5RvHVW8I0prJA/out-0.webp" ], "started_at": "2024-08-28T20:26:37.452434Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/zaxv8e9p09rm40chkant8n1fdw", "cancel": "https://api.replicate.com/v1/predictions/zaxv8e9p09rm40chkant8n1fdw/cancel" }, "version": "c13123731b41d7d2265ba4b6ea251b0f018aa254fc6a79dac3079578fe848ea3" }Generated inUsing seed: 29949 Prompt: ARCHSLRA a warrior holding the head of his enemy, on the blackened grass battlefield at night txt2img mode Using dev model free=9093396889600 Downloading weights 2024-08-28T20:26:37Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp7uynhdk0/weights url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar 2024-08-28T20:26:39Z | INFO | [ Complete ] dest=/tmp/tmp7uynhdk0/weights size="172 MB" total_elapsed=1.698s url=https://replicate.delivery/yhqm/zr6nLoCQgfwVQ6abnfHcezspFpKrofN47o9EIielOI76uK4aC/trained_model.tar Downloaded weights in 1.80s Loaded LoRAs in 10.92s 0%| | 0/34 [00:00<?, ?it/s] 3%|▎ | 1/34 [00:00<00:08, 3.68it/s] 6%|▌ | 2/34 [00:00<00:07, 4.24it/s] 9%|▉ | 3/34 [00:00<00:07, 3.96it/s] 12%|█▏ | 4/34 [00:01<00:07, 3.84it/s] 15%|█▍ | 5/34 [00:01<00:07, 3.78it/s] 18%|█▊ | 6/34 [00:01<00:07, 3.74it/s] 21%|██ | 7/34 [00:01<00:07, 3.72it/s] 24%|██▎ | 8/34 [00:02<00:07, 3.71it/s] 26%|██▋ | 9/34 [00:02<00:06, 3.70it/s] 29%|██▉ | 10/34 [00:02<00:06, 3.69it/s] 32%|███▏ | 11/34 [00:02<00:06, 3.69it/s] 35%|███▌ | 12/34 [00:03<00:05, 3.69it/s] 38%|███▊ | 13/34 [00:03<00:05, 3.69it/s] 41%|████ | 14/34 [00:03<00:05, 3.69it/s] 44%|████▍ | 15/34 [00:04<00:05, 3.69it/s] 47%|████▋ | 16/34 [00:04<00:04, 3.69it/s] 50%|█████ | 17/34 [00:04<00:04, 3.69it/s] 53%|█████▎ | 18/34 [00:04<00:04, 3.68it/s] 56%|█████▌ | 19/34 [00:05<00:04, 3.69it/s] 59%|█████▉ | 20/34 [00:05<00:03, 3.69it/s] 62%|██████▏ | 21/34 [00:05<00:03, 3.69it/s] 65%|██████▍ | 22/34 [00:05<00:03, 3.69it/s] 68%|██████▊ | 23/34 [00:06<00:02, 3.69it/s] 71%|███████ | 24/34 [00:06<00:02, 3.69it/s] 74%|███████▎ | 25/34 [00:06<00:02, 3.69it/s] 76%|███████▋ | 26/34 [00:06<00:02, 3.68it/s] 79%|███████▉ | 27/34 [00:07<00:01, 3.69it/s] 82%|████████▏ | 28/34 [00:07<00:01, 3.69it/s] 85%|████████▌ | 29/34 [00:07<00:01, 3.69it/s] 88%|████████▊ | 30/34 [00:08<00:01, 3.69it/s] 91%|█████████ | 31/34 [00:08<00:00, 3.69it/s] 94%|█████████▍| 32/34 [00:08<00:00, 3.69it/s] 97%|█████████▋| 33/34 [00:08<00:00, 3.69it/s] 100%|██████████| 34/34 [00:09<00:00, 3.69it/s] 100%|██████████| 34/34 [00:09<00:00, 3.71it/s]
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