black-forest-labs / flux-dev-lora
A version of flux-dev, a text to image model, that supports fast fine-tuned lora inference (Updated 3 weeks, 4 days ago)
Prediction
black-forest-labs/flux-dev-loraOfficial modelID30k587n6shrme0ck4zzrr6bt6cStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- a bacon cheeseburger in the style of TOK a trtcrd, tarot style
- go_fast
- guidance
- 3
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- lora_weights
- huggingface.co/multimodalart/flux-tarot-v1
- output_format
- webp
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "a bacon cheeseburger in the style of TOK a trtcrd, tarot style", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/multimodalart/flux-tarot-v1", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "a bacon cheeseburger in the style of TOK a trtcrd, tarot style", go_fast: true, guidance: 3, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", lora_weights: "huggingface.co/multimodalart/flux-tarot-v1", output_format: "webp", output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 }; const output = await replicate.run("black-forest-labs/flux-dev-lora", { input }); // 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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "black-forest-labs/flux-dev-lora", input={ "prompt": "a bacon cheeseburger in the style of TOK a trtcrd, tarot style", "go_fast": True, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/multimodalart/flux-tarot-v1", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run black-forest-labs/flux-dev-lora 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 $'{ "input": { "prompt": "a bacon cheeseburger in the style of TOK a trtcrd, tarot style", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/multimodalart/flux-tarot-v1", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/models/black-forest-labs/flux-dev-lora/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-14T00:08:08.972441Z", "created_at": "2024-11-14T00:08:06.092000Z", "data_removed": false, "error": null, "id": "30k587n6shrme0ck4zzrr6bt6c", "input": { "prompt": "a bacon cheeseburger in the style of TOK a trtcrd, tarot style", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/multimodalart/flux-tarot-v1", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Lora huggingface.co/multimodalart/flux-tarot-v1 already loaded\nrunning quantized prediction\nUsing seed: 1813648211\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 17.76it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 12.89it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.82it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.39it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.14it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.75it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.72it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.71it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.72it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.72it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.53it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.53it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.58it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.61it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.92it/s]\nTotal safe images: 1 out of 1", "metrics": { "image_count": 1, "predict_time": 2.874607308, "total_time": 2.880441 }, "output": [ "https://replicate.delivery/xezq/MIF2XaWOzOZ7DVu4KsxRv4US2mHxoSWYlCeiiFCS78foFvwTA/out-0.webp" ], "started_at": "2024-11-14T00:08:06.097833Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-bsppfm5v4e5ceihotnxcgaoabro3jzmpo3fc2dvv5are2znbsokq", "get": "https://api.replicate.com/v1/predictions/30k587n6shrme0ck4zzrr6bt6c", "cancel": "https://api.replicate.com/v1/predictions/30k587n6shrme0ck4zzrr6bt6c/cancel" }, "version": "hidden" }
Generated inLora huggingface.co/multimodalart/flux-tarot-v1 already loaded running quantized prediction Using seed: 1813648211 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 17.76it/s] 14%|█▍ | 4/28 [00:00<00:01, 12.89it/s] 21%|██▏ | 6/28 [00:00<00:01, 11.82it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.39it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.14it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.75it/s] 50%|█████ | 14/28 [00:01<00:01, 10.72it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.71it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.72it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.72it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.53it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.53it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.58it/s] 100%|██████████| 28/28 [00:02<00:00, 10.61it/s] 100%|██████████| 28/28 [00:02<00:00, 10.92it/s] Total safe images: 1 out of 1
Prediction
black-forest-labs/flux-dev-loraOfficial modelIDa0nn5pvxrdrmc0ck504acd609cStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- style of 80s cyberpunk, a portrait photo
- go_fast
- guidance
- 3
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- lora_weights
- fofr/flux-80s-cyberpunk
- output_format
- webp
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "style of 80s cyberpunk, a portrait photo", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "fofr/flux-80s-cyberpunk", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "style of 80s cyberpunk, a portrait photo", go_fast: true, guidance: 3, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", lora_weights: "fofr/flux-80s-cyberpunk", output_format: "webp", output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 }; const output = await replicate.run("black-forest-labs/flux-dev-lora", { input }); // 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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "black-forest-labs/flux-dev-lora", input={ "prompt": "style of 80s cyberpunk, a portrait photo", "go_fast": True, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "fofr/flux-80s-cyberpunk", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run black-forest-labs/flux-dev-lora 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 $'{ "input": { "prompt": "style of 80s cyberpunk, a portrait photo", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "fofr/flux-80s-cyberpunk", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/models/black-forest-labs/flux-dev-lora/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-14T00:17:48.247218Z", "created_at": "2024-11-14T00:17:45.411000Z", "data_removed": false, "error": null, "id": "a0nn5pvxrdrmc0ck504acd609c", "input": { "prompt": "style of 80s cyberpunk, a portrait photo", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "fofr/flux-80s-cyberpunk", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Lora fofr/flux-80s-cyberpunk already loaded\nrunning quantized prediction\nUsing seed: 1827486286\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.09it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.05it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.97it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.50it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.25it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.86it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.83it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.83it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.84it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.81it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.69it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.68it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.71it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.73it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.05it/s]\nTotal safe images: 1 out of 1", "metrics": { "image_count": 1, "predict_time": 2.831174012, "total_time": 2.836218 }, "output": [ "https://replicate.delivery/xezq/a43wloJrIDpoJpCH81EfhI00PbQrmhpfpUWqCvZPtWEsOvwTA/out-0.webp" ], "started_at": "2024-11-14T00:17:45.416044Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-q3ffcsvkewovj6bohktwae5k4x4moko5y3k5ofshtgeb3fc6hviq", "get": "https://api.replicate.com/v1/predictions/a0nn5pvxrdrmc0ck504acd609c", "cancel": "https://api.replicate.com/v1/predictions/a0nn5pvxrdrmc0ck504acd609c/cancel" }, "version": "hidden" }
Generated inLora fofr/flux-80s-cyberpunk already loaded running quantized prediction Using seed: 1827486286 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 18.09it/s] 14%|█▍ | 4/28 [00:00<00:01, 13.05it/s] 21%|██▏ | 6/28 [00:00<00:01, 11.97it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.50it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.25it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.86it/s] 50%|█████ | 14/28 [00:01<00:01, 10.83it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.83it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.84it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.81it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.69it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.68it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.71it/s] 100%|██████████| 28/28 [00:02<00:00, 10.73it/s] 100%|██████████| 28/28 [00:02<00:00, 11.05it/s] Total safe images: 1 out of 1
Prediction
black-forest-labs/flux-dev-loraOfficial modelIDh1nykv9z3drme0ck506ay2gjyrStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll
- go_fast
- guidance
- 3
- lora_scale
- 0.7
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- lora_weights
- davisbrown/flux-half-illustration
- output_format
- webp
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "go_fast": true, "guidance": 3, "lora_scale": 0.7, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "davisbrown/flux-half-illustration", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", go_fast: true, guidance: 3, lora_scale: 0.7, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", lora_weights: "davisbrown/flux-half-illustration", output_format: "webp", output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 }; const output = await replicate.run("black-forest-labs/flux-dev-lora", { input }); // 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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "black-forest-labs/flux-dev-lora", input={ "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "go_fast": True, "guidance": 3, "lora_scale": 0.7, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "davisbrown/flux-half-illustration", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run black-forest-labs/flux-dev-lora 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 $'{ "input": { "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "go_fast": true, "guidance": 3, "lora_scale": 0.7, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "davisbrown/flux-half-illustration", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/models/black-forest-labs/flux-dev-lora/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-14T00:21:54.387601Z", "created_at": "2024-11-14T00:21:51.515000Z", "data_removed": false, "error": null, "id": "h1nykv9z3drme0ck506ay2gjyr", "input": { "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "go_fast": true, "guidance": 3, "lora_scale": 0.7, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "davisbrown/flux-half-illustration", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Lora davisbrown/flux-half-illustration already loaded\nrunning quantized prediction\nUsing seed: 3287284191\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 17.81it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 12.93it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.87it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.45it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.20it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.83it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.83it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.78it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.78it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.76it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.65it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.63it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.64it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.66it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.99it/s]\nTotal safe images: 1 out of 1", "metrics": { "image_count": 1, "predict_time": 2.866995538, "total_time": 2.872601 }, "output": [ "https://replicate.delivery/xezq/v9eRgadlfiqktkbyFy4R6ki6LTBJSYvkpsBHbLxmrPViSvwTA/out-0.webp" ], "started_at": "2024-11-14T00:21:51.520605Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-lxfcbwtkjxau7zcdzsqewijy5ha26bambvx7ykrlbkjqbarqlz6q", "get": "https://api.replicate.com/v1/predictions/h1nykv9z3drme0ck506ay2gjyr", "cancel": "https://api.replicate.com/v1/predictions/h1nykv9z3drme0ck506ay2gjyr/cancel" }, "version": "hidden" }
Generated inLora davisbrown/flux-half-illustration already loaded running quantized prediction Using seed: 3287284191 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 17.81it/s] 14%|█▍ | 4/28 [00:00<00:01, 12.93it/s] 21%|██▏ | 6/28 [00:00<00:01, 11.87it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.45it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.20it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.83it/s] 50%|█████ | 14/28 [00:01<00:01, 10.83it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.78it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.78it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.76it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.65it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.63it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.64it/s] 100%|██████████| 28/28 [00:02<00:00, 10.66it/s] 100%|██████████| 28/28 [00:02<00:00, 10.99it/s] Total safe images: 1 out of 1
Prediction
black-forest-labs/flux-dev-loraOfficial modelID55tgxa28qxrm80ck50996j6yzgStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, flmft style
- go_fast
- guidance
- 3
- lora_scale
- 0.9
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- lora_weights
- huggingface.co/alvdansen/flux-koda
- output_format
- webp
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, flmft style", "go_fast": true, "guidance": 3, "lora_scale": 0.9, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/alvdansen/flux-koda", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, flmft style", go_fast: true, guidance: 3, lora_scale: 0.9, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", lora_weights: "huggingface.co/alvdansen/flux-koda", output_format: "webp", output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 }; const output = await replicate.run("black-forest-labs/flux-dev-lora", { input }); // 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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "black-forest-labs/flux-dev-lora", input={ "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, flmft style", "go_fast": True, "guidance": 3, "lora_scale": 0.9, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/alvdansen/flux-koda", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run black-forest-labs/flux-dev-lora 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 $'{ "input": { "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, flmft style", "go_fast": true, "guidance": 3, "lora_scale": 0.9, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/alvdansen/flux-koda", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/models/black-forest-labs/flux-dev-lora/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-14T00:28:30.579241Z", "created_at": "2024-11-14T00:28:27.199000Z", "data_removed": false, "error": null, "id": "55tgxa28qxrm80ck50996j6yzg", "input": { "prompt": "A tabby cat lounging on a sun-dappled windowsill, half its body in shadow, half in bright light, flmft style", "go_fast": true, "guidance": 3, "lora_scale": 0.9, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "huggingface.co/alvdansen/flux-koda", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "2024-11-14 00:28:27.205 | DEBUG | fp8.lora_loading:apply_lora_to_model:547 - Extracting keys\n2024-11-14 00:28:27.205 | DEBUG | fp8.lora_loading:apply_lora_to_model:554 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13354.16it/s]\n2024-11-14 00:28:27.228 | SUCCESS | fp8.lora_loading:unload_loras:537 - LoRAs unloaded in 0.023s\n2024-11-14 00:28:27.231 | INFO | fp8.lora_loading:load_lora:497 - Loading LoRA weights for /src/weights-cache/31eaaa0241aa1ad5\n2024-11-14 00:28:27.384 | INFO | fp8.lora_loading:load_lora:518 - LoRA weights loaded\n2024-11-14 00:28:27.384 | DEBUG | fp8.lora_loading:apply_lora_to_model:547 - Extracting keys\n2024-11-14 00:28:27.384 | DEBUG | fp8.lora_loading:apply_lora_to_model:554 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 41%|████ | 125/304 [00:00<00:00, 1248.30it/s]\nApplying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 954.60it/s] \nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 967.09it/s]\n2024-11-14 00:28:27.699 | SUCCESS | fp8.lora_loading:load_lora:521 - LoRA applied in 0.47s\nrunning quantized prediction\nUsing seed: 1541013700\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.02it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 12.97it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.90it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.47it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.09it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.83it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.83it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.82it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.82it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.78it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.67it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.69it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.73it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.73it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.03it/s]\nTotal safe images: 1 out of 1", "metrics": { "image_count": 1, "predict_time": 3.374442034, "total_time": 3.380241 }, "output": [ "https://replicate.delivery/xezq/YumehO0CBftCZUz9ubFKRXBGU3ZOePKrD7TivvfeUOW1F7FeE/out-0.webp" ], "started_at": "2024-11-14T00:28:27.204799Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-4p76hgchoqzr65twu5srquso5xyww7i2veovf3hngdxdlp6nwkja", "get": "https://api.replicate.com/v1/predictions/55tgxa28qxrm80ck50996j6yzg", "cancel": "https://api.replicate.com/v1/predictions/55tgxa28qxrm80ck50996j6yzg/cancel" }, "version": "hidden" }
Generated in2024-11-14 00:28:27.205 | DEBUG | fp8.lora_loading:apply_lora_to_model:547 - Extracting keys 2024-11-14 00:28:27.205 | DEBUG | fp8.lora_loading:apply_lora_to_model:554 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 13354.16it/s] 2024-11-14 00:28:27.228 | SUCCESS | fp8.lora_loading:unload_loras:537 - LoRAs unloaded in 0.023s 2024-11-14 00:28:27.231 | INFO | fp8.lora_loading:load_lora:497 - Loading LoRA weights for /src/weights-cache/31eaaa0241aa1ad5 2024-11-14 00:28:27.384 | INFO | fp8.lora_loading:load_lora:518 - LoRA weights loaded 2024-11-14 00:28:27.384 | DEBUG | fp8.lora_loading:apply_lora_to_model:547 - Extracting keys 2024-11-14 00:28:27.384 | DEBUG | fp8.lora_loading:apply_lora_to_model:554 - Keys extracted Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s] Applying LoRA: 41%|████ | 125/304 [00:00<00:00, 1248.30it/s] Applying LoRA: 82%|████████▏ | 250/304 [00:00<00:00, 954.60it/s] Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 967.09it/s] 2024-11-14 00:28:27.699 | SUCCESS | fp8.lora_loading:load_lora:521 - LoRA applied in 0.47s running quantized prediction Using seed: 1541013700 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 18.02it/s] 14%|█▍ | 4/28 [00:00<00:01, 12.97it/s] 21%|██▏ | 6/28 [00:00<00:01, 11.90it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.47it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.09it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.83it/s] 50%|█████ | 14/28 [00:01<00:01, 10.83it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.82it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.82it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.78it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.67it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.69it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.73it/s] 100%|██████████| 28/28 [00:02<00:00, 10.73it/s] 100%|██████████| 28/28 [00:02<00:00, 11.03it/s] Total safe images: 1 out of 1
Prediction
black-forest-labs/flux-dev-loraOfficial modelID4ebhhnyj5xrma0ckdxqt30qcsgStatusSucceededSourceWebTotal durationCreatedInput
- prompt
- pnt style Illustration of a latina woman
- go_fast
- guidance
- 3
- lora_scale
- 1
- megapixels
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- lora_weights
- https://civitai.com/api/download/models/735262
- output_format
- webp
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "pnt style Illustration of a latina woman", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "https://civitai.com/api/download/models/735262", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const input = { prompt: "pnt style Illustration of a latina woman", go_fast: true, guidance: 3, lora_scale: 1, megapixels: "1", num_outputs: 1, aspect_ratio: "1:1", lora_weights: "https://civitai.com/api/download/models/735262", output_format: "webp", output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 }; const output = await replicate.run("black-forest-labs/flux-dev-lora", { input }); // 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 black-forest-labs/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "black-forest-labs/flux-dev-lora", input={ "prompt": "pnt style Illustration of a latina woman", "go_fast": True, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "https://civitai.com/api/download/models/735262", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run black-forest-labs/flux-dev-lora 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 $'{ "input": { "prompt": "pnt style Illustration of a latina woman", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "https://civitai.com/api/download/models/735262", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/models/black-forest-labs/flux-dev-lora/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-11-27T21:03:42.410975Z", "created_at": "2024-11-27T21:03:39.567000Z", "data_removed": false, "error": null, "id": "4ebhhnyj5xrma0ckdxqt30qcsg", "input": { "prompt": "pnt style Illustration of a latina woman", "go_fast": true, "guidance": 3, "lora_scale": 1, "megapixels": "1", "num_outputs": 1, "aspect_ratio": "1:1", "lora_weights": "https://civitai.com/api/download/models/735262", "output_format": "webp", "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Lora https://civitai.com/api/download/models/735262 already loaded\nrunning quantized prediction\nUsing seed: 146917677\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 17.89it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 12.99it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 11.98it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.54it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.29it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.89it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.84it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.85it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.86it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.86it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.74it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.71it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.73it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.78it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.08it/s]\nTotal safe images: 1 out of 1", "metrics": { "image_count": 1, "predict_time": 2.83643081, "total_time": 2.843975 }, "output": [ "https://replicate.delivery/xezq/skK7077kxy5ecKHxoG4Ls20ULdomyso9sxzfambkuegdZnqnA/out-0.webp" ], "started_at": "2024-11-27T21:03:39.574544Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-qgz7m4d2w7o7pozm7mdnkp63n6zaoplutudcvnydz7x7tkx63bgq", "get": "https://api.replicate.com/v1/predictions/4ebhhnyj5xrma0ckdxqt30qcsg", "cancel": "https://api.replicate.com/v1/predictions/4ebhhnyj5xrma0ckdxqt30qcsg/cancel" }, "version": "hidden" }
Generated inLora https://civitai.com/api/download/models/735262 already loaded running quantized prediction Using seed: 146917677 0%| | 0/28 [00:00<?, ?it/s] 7%|▋ | 2/28 [00:00<00:01, 17.89it/s] 14%|█▍ | 4/28 [00:00<00:01, 12.99it/s] 21%|██▏ | 6/28 [00:00<00:01, 11.98it/s] 29%|██▊ | 8/28 [00:00<00:01, 11.54it/s] 36%|███▌ | 10/28 [00:00<00:01, 11.29it/s] 43%|████▎ | 12/28 [00:01<00:01, 10.89it/s] 50%|█████ | 14/28 [00:01<00:01, 10.84it/s] 57%|█████▋ | 16/28 [00:01<00:01, 10.85it/s] 64%|██████▍ | 18/28 [00:01<00:00, 10.86it/s] 71%|███████▏ | 20/28 [00:01<00:00, 10.86it/s] 79%|███████▊ | 22/28 [00:01<00:00, 10.74it/s] 86%|████████▌ | 24/28 [00:02<00:00, 10.71it/s] 93%|█████████▎| 26/28 [00:02<00:00, 10.73it/s] 100%|██████████| 28/28 [00:02<00:00, 10.78it/s] 100%|██████████| 28/28 [00:02<00:00, 11.08it/s] Total safe images: 1 out of 1
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