fofr / flux-80s-cyberpunk
A flux lora trained on a 1980s cyberpunk aesthetic
- Public
- 5K runs
-
H100
Prediction
fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180Input
- model
- dev
- prompt
- style of 80s cyberpunk, a portrait photo
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 2:3
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "style of 80s cyberpunk, a portrait photo", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 fofr/flux-80s-cyberpunk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", { input: { model: "dev", prompt: "style of 80s cyberpunk, a portrait photo", lora_scale: 1, num_outputs: 1, aspect_ratio: "2:3", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 replicate
Import the client:import replicate
Run fofr/flux-80s-cyberpunk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", input={ "model": "dev", "prompt": "style of 80s cyberpunk, a portrait photo", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-80s-cyberpunk 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": "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", "input": { "model": "dev", "prompt": "style of 80s cyberpunk, a portrait photo", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-15T17:28:39.915657Z", "created_at": "2024-08-15T17:28:19.961000Z", "data_removed": false, "error": null, "id": "fqwhvyaez5rm60chawartrygc0", "input": { "model": "dev", "prompt": "style of 80s cyberpunk, a portrait photo", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 32965\nPrompt: style of 80s cyberpunk, a portrait photo\ntxt2img mode\nUsing dev model\nLoading LoRA weights from https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\nEnsuring enough disk space...\nFree disk space: 9726596481024\nDownloading weights: https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\n2024-08-15T17:28:21Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d2a6f09ee8ecaf46 url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\n2024-08-15T17:28:24Z | INFO | [ Complete ] dest=/src/weights-cache/d2a6f09ee8ecaf46 size=\"172 MB\" total_elapsed=2.874s url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\nb''\nDownloaded weights in 2.902064800262451 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.75it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.31it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.05it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.93it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.85it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.81it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.80it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.78it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.76it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.75it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.76it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.76it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.75it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.74it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.75it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.75it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.74it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.74it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.74it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.75it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.74it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.74it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.74it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.75it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.74it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.74it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.74it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.74it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.77it/s]", "metrics": { "predict_time": 18.61833491, "total_time": 19.954657 }, "output": [ "https://replicate.delivery/yhqm/QD8Ioy5NExqSCtBS8hG04XIRQZFaC9pxJemINT1bibyjZfSTA/out-0.webp" ], "started_at": "2024-08-15T17:28:21.297322Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fqwhvyaez5rm60chawartrygc0", "cancel": "https://api.replicate.com/v1/predictions/fqwhvyaez5rm60chawartrygc0/cancel" }, "version": "5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180" }
Generated inUsing seed: 32965 Prompt: style of 80s cyberpunk, a portrait photo txt2img mode Using dev model Loading LoRA weights from https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar Ensuring enough disk space... Free disk space: 9726596481024 Downloading weights: https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar 2024-08-15T17:28:21Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d2a6f09ee8ecaf46 url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar 2024-08-15T17:28:24Z | INFO | [ Complete ] dest=/src/weights-cache/d2a6f09ee8ecaf46 size="172 MB" total_elapsed=2.874s url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar b'' Downloaded weights in 2.902064800262451 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.75it/s] 7%|▋ | 2/28 [00:00<00:06, 4.31it/s] 11%|█ | 3/28 [00:00<00:06, 4.05it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.93it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.85it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.81it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.80it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.78it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.76it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.75it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.76it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.76it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.75it/s] 50%|█████ | 14/28 [00:03<00:03, 3.74it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.75it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.75it/s] 61%|██████ | 17/28 [00:04<00:02, 3.74it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.74it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.74it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.75it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.74it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.74it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.74it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.75it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.74it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.74it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.74it/s] 100%|██████████| 28/28 [00:07<00:00, 3.74it/s] 100%|██████████| 28/28 [00:07<00:00, 3.77it/s]
Prediction
fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180IDahh74kkm3hrm20chawcv9cswjrStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- style of 80s cyberpunk, a living room interior
- lora_scale
- 0.7
- num_outputs
- 1
- aspect_ratio
- 2:3
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "style of 80s cyberpunk, a living room interior", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 fofr/flux-80s-cyberpunk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", { input: { model: "dev", prompt: "style of 80s cyberpunk, a living room interior", lora_scale: 0.7, num_outputs: 1, aspect_ratio: "2:3", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 replicate
Import the client:import replicate
Run fofr/flux-80s-cyberpunk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", input={ "model": "dev", "prompt": "style of 80s cyberpunk, a living room interior", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-80s-cyberpunk 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": "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", "input": { "model": "dev", "prompt": "style of 80s cyberpunk, a living room interior", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-15T17:33:09.850655Z", "created_at": "2024-08-15T17:32:51.612000Z", "data_removed": false, "error": null, "id": "ahh74kkm3hrm20chawcv9cswjr", "input": { "model": "dev", "prompt": "style of 80s cyberpunk, a living room interior", "lora_scale": 0.7, "num_outputs": 1, "aspect_ratio": "2:3", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 14682\nPrompt: style of 80s cyberpunk, a living room interior\ntxt2img mode\nUsing dev model\nLoading LoRA weights from https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.59it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.02it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.81it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.72it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.68it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.65it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.63it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.62it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.61it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.61it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.60it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.60it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.60it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.60it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.60it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.59it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.59it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.60it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.60it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.60it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.61it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.61it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.61it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.60it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.61it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.61it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.61it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.61it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.62it/s]", "metrics": { "predict_time": 16.351830026000002, "total_time": 18.238655 }, "output": [ "https://replicate.delivery/yhqm/pDI3aW5ln04xDFiQHGoWHQ9KfNZBou4zeGs6MeuNSPrqu9lmA/out-0.webp" ], "started_at": "2024-08-15T17:32:53.498825Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ahh74kkm3hrm20chawcv9cswjr", "cancel": "https://api.replicate.com/v1/predictions/ahh74kkm3hrm20chawcv9cswjr/cancel" }, "version": "5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180" }
Generated inUsing seed: 14682 Prompt: style of 80s cyberpunk, a living room interior txt2img mode Using dev model Loading LoRA weights from https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.59it/s] 7%|▋ | 2/28 [00:00<00:06, 4.02it/s] 11%|█ | 3/28 [00:00<00:06, 3.81it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.72it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.68it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.65it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.63it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.62it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.61it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.61it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.60it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.60it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.60it/s] 50%|█████ | 14/28 [00:03<00:03, 3.60it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.60it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.59it/s] 61%|██████ | 17/28 [00:04<00:03, 3.59it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.60it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.60it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.60it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.61it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.61it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.61it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.60it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.61it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.61it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.61it/s] 100%|██████████| 28/28 [00:07<00:00, 3.61it/s] 100%|██████████| 28/28 [00:07<00:00, 3.62it/s]
Prediction
fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180ID06a3js4xvxrm00chawdb4h7d2rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- style of 80s cyberpunk, a car
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:2
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "style of 80s cyberpunk, a car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
Import 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 fofr/flux-80s-cyberpunk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", { input: { model: "dev", prompt: "style of 80s cyberpunk, a car", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:2", output_format: "webp", guidance_scale: 3.5, output_quality: 80, 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 replicate
Import the client:import replicate
Run fofr/flux-80s-cyberpunk using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", input={ "model": "dev", "prompt": "style of 80s cyberpunk, a car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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 fofr/flux-80s-cyberpunk 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": "fofr/flux-80s-cyberpunk:5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180", "input": { "model": "dev", "prompt": "style of 80s cyberpunk, a car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-08-15T17:34:30.843421Z", "created_at": "2024-08-15T17:34:07.839000Z", "data_removed": false, "error": null, "id": "06a3js4xvxrm00chawdb4h7d2r", "input": { "model": "dev", "prompt": "style of 80s cyberpunk, a car", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:2", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 43032\nPrompt: style of 80s cyberpunk, a car\ntxt2img mode\nUsing dev model\nLoading LoRA weights from https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\nEnsuring enough disk space...\nFree disk space: 9410334429184\nDownloading weights: https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\n2024-08-15T17:34:10Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d2a6f09ee8ecaf46 url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\n2024-08-15T17:34:12Z | INFO | [ Complete ] dest=/src/weights-cache/d2a6f09ee8ecaf46 size=\"172 MB\" total_elapsed=1.681s url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar\nb''\nDownloaded weights in 1.7085769176483154 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:09, 2.99it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.85it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.82it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.80it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.78it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.78it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.78it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.78it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.78it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.78it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.77it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.77it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.77it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.77it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.77it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.77it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.77it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.77it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.77it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.77it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.77it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.77it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.77it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.77it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.77it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.77it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.76it/s]", "metrics": { "predict_time": 20.433721259, "total_time": 23.004421 }, "output": [ "https://replicate.delivery/yhqm/x2q8ZM0ifR2bSyarmshIz3KqrGBWQwRUzfshF8BJAqvm4elmA/out-0.webp" ], "started_at": "2024-08-15T17:34:10.409700Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/06a3js4xvxrm00chawdb4h7d2r", "cancel": "https://api.replicate.com/v1/predictions/06a3js4xvxrm00chawdb4h7d2r/cancel" }, "version": "5d0cefd0746b833042b384c3a310bc4d1f9d1304ec59ba93e75097d40b967180" }
Generated inUsing seed: 43032 Prompt: style of 80s cyberpunk, a car txt2img mode Using dev model Loading LoRA weights from https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar Ensuring enough disk space... Free disk space: 9410334429184 Downloading weights: https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar 2024-08-15T17:34:10Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/d2a6f09ee8ecaf46 url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar 2024-08-15T17:34:12Z | INFO | [ Complete ] dest=/src/weights-cache/d2a6f09ee8ecaf46 size="172 MB" total_elapsed=1.681s url=https://replicate.delivery/yhqm/DDR8uNjZIRZrChCj3jFgxcjMvgyGZcAolnnE7YEva8cEPv0E/trained_model.tar b'' Downloaded weights in 1.7085769176483154 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.99it/s] 7%|▋ | 2/28 [00:00<00:06, 3.85it/s] 11%|█ | 3/28 [00:00<00:06, 3.82it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.80it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.79it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.78it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.78it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.78it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.78it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.78it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.78it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.78it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.77it/s] 50%|█████ | 14/28 [00:03<00:03, 3.77it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.77it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.77it/s] 61%|██████ | 17/28 [00:04<00:02, 3.77it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.77it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.77it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.77it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.77it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.77it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.77it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.77it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.77it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.77it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.77it/s] 100%|██████████| 28/28 [00:07<00:00, 3.77it/s] 100%|██████████| 28/28 [00:07<00:00, 3.76it/s]
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