lucataco / flux-dev-lora
FLUX.1-Dev LoRA Explorer (DEPRECATED Please use: black-forest-labs/flux-dev-lora) (Updated 8 months, 1 week ago)
Prediction
lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3IDem16szn9ysrj20ckgzzss99wvrStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedby @lucatacoInput
- prompt
- a beautiful castle frstingln illustration
- hf_lora
- alvdansen/frosting_lane_flux
- lora_scale
- 0.8
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "a beautiful castle frstingln illustration", "hf_lora": "alvdansen/frosting_lane_flux", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", { input: { prompt: "a beautiful castle frstingln illustration", hf_lora: "alvdansen/frosting_lane_flux", lora_scale: 0.8, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input={ "prompt": "a beautiful castle frstingln illustration", "hf_lora": "alvdansen/frosting_lane_flux", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "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 lucataco/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 $'{ "version": "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", "input": { "prompt": "a beautiful castle frstingln illustration", "hf_lora": "alvdansen/frosting_lane_flux", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-02T15:31:58.179554Z", "created_at": "2024-12-02T15:31:39.638000Z", "data_removed": false, "error": null, "id": "em16szn9ysrj20ckgzzss99wvr", "input": { "prompt": "a beautiful castle frstingln illustration", "hf_lora": "alvdansen/frosting_lane_flux", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 15405\nPrompt: a beautiful castle frstingln illustration\ntxt2img mode\nLoading LoRA took: 0.00 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:17, 1.53it/s]\n 7%|▋ | 2/28 [00:01<00:15, 1.70it/s]\n 11%|█ | 3/28 [00:01<00:15, 1.63it/s]\n 14%|█▍ | 4/28 [00:02<00:15, 1.60it/s]\n 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s]\n 21%|██▏ | 6/28 [00:03<00:14, 1.57it/s]\n 25%|██▌ | 7/28 [00:04<00:13, 1.56it/s]\n 29%|██▊ | 8/28 [00:05<00:12, 1.56it/s]\n 32%|███▏ | 9/28 [00:05<00:12, 1.55it/s]\n 36%|███▌ | 10/28 [00:06<00:11, 1.55it/s]\n 39%|███▉ | 11/28 [00:07<00:10, 1.55it/s]\n 43%|████▎ | 12/28 [00:07<00:10, 1.55it/s]\n 46%|████▋ | 13/28 [00:08<00:09, 1.55it/s]\n 50%|█████ | 14/28 [00:08<00:09, 1.55it/s]\n 54%|█████▎ | 15/28 [00:09<00:08, 1.55it/s]\n 57%|█████▋ | 16/28 [00:10<00:07, 1.55it/s]\n 61%|██████ | 17/28 [00:10<00:07, 1.55it/s]\n 64%|██████▍ | 18/28 [00:11<00:06, 1.55it/s]\n 68%|██████▊ | 19/28 [00:12<00:05, 1.55it/s]\n 71%|███████▏ | 20/28 [00:12<00:05, 1.55it/s]\n 75%|███████▌ | 21/28 [00:13<00:04, 1.55it/s]\n 79%|███████▊ | 22/28 [00:14<00:03, 1.55it/s]\n 82%|████████▏ | 23/28 [00:14<00:03, 1.55it/s]\n 86%|████████▌ | 24/28 [00:15<00:02, 1.55it/s]\n 89%|████████▉ | 25/28 [00:16<00:01, 1.55it/s]\n 93%|█████████▎| 26/28 [00:16<00:01, 1.55it/s]\n 96%|█████████▋| 27/28 [00:17<00:00, 1.55it/s]\n100%|██████████| 28/28 [00:17<00:00, 1.55it/s]\n100%|██████████| 28/28 [00:17<00:00, 1.56it/s]", "metrics": { "predict_time": 18.533655572, "total_time": 18.541554 }, "output": [ "https://replicate.delivery/yhqm/0WLq8ncyUCZRLlofeOqT96FjGFfPfm4ECTV3ieAaLLjzdC3eE/out-0.webp" ], "started_at": "2024-12-02T15:31:39.645899Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-thrhoazcuhblomq4hwjjiv3ogotcvdr7e6vgbmxvtklm3p7d3zpa", "get": "https://api.replicate.com/v1/predictions/em16szn9ysrj20ckgzzss99wvr", "cancel": "https://api.replicate.com/v1/predictions/em16szn9ysrj20ckgzzss99wvr/cancel" }, "version": "091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3" }Generated inUsing seed: 15405 Prompt: a beautiful castle frstingln illustration txt2img mode Loading LoRA took: 0.00 seconds 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:17, 1.53it/s] 7%|▋ | 2/28 [00:01<00:15, 1.70it/s] 11%|█ | 3/28 [00:01<00:15, 1.63it/s] 14%|█▍ | 4/28 [00:02<00:15, 1.60it/s] 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s] 21%|██▏ | 6/28 [00:03<00:14, 1.57it/s] 25%|██▌ | 7/28 [00:04<00:13, 1.56it/s] 29%|██▊ | 8/28 [00:05<00:12, 1.56it/s] 32%|███▏ | 9/28 [00:05<00:12, 1.55it/s] 36%|███▌ | 10/28 [00:06<00:11, 1.55it/s] 39%|███▉ | 11/28 [00:07<00:10, 1.55it/s] 43%|████▎ | 12/28 [00:07<00:10, 1.55it/s] 46%|████▋ | 13/28 [00:08<00:09, 1.55it/s] 50%|█████ | 14/28 [00:08<00:09, 1.55it/s] 54%|█████▎ | 15/28 [00:09<00:08, 1.55it/s] 57%|█████▋ | 16/28 [00:10<00:07, 1.55it/s] 61%|██████ | 17/28 [00:10<00:07, 1.55it/s] 64%|██████▍ | 18/28 [00:11<00:06, 1.55it/s] 68%|██████▊ | 19/28 [00:12<00:05, 1.55it/s] 71%|███████▏ | 20/28 [00:12<00:05, 1.55it/s] 75%|███████▌ | 21/28 [00:13<00:04, 1.55it/s] 79%|███████▊ | 22/28 [00:14<00:03, 1.55it/s] 82%|████████▏ | 23/28 [00:14<00:03, 1.55it/s] 86%|████████▌ | 24/28 [00:15<00:02, 1.55it/s] 89%|████████▉ | 25/28 [00:16<00:01, 1.55it/s] 93%|█████████▎| 26/28 [00:16<00:01, 1.55it/s] 96%|█████████▋| 27/28 [00:17<00:00, 1.55it/s] 100%|██████████| 28/28 [00:17<00:00, 1.55it/s] 100%|██████████| 28/28 [00:17<00:00, 1.56it/s]Prediction
lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3IDgtv3ht2wf1rj00ckh0083jez2mStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedby @lucatacoInput
- prompt
- portrait photo of QSO dog
- hf_lora
- https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "portrait photo of QSO dog", "hf_lora": "https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", { input: { prompt: "portrait photo of QSO dog", hf_lora: "https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar", lora_scale: 1, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input={ "prompt": "portrait photo of QSO dog", "hf_lora": "https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "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 lucataco/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 $'{ "version": "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", "input": { "prompt": "portrait photo of QSO dog", "hf_lora": "https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-02T15:32:41.186704Z", "created_at": "2024-12-02T15:32:25.336000Z", "data_removed": false, "error": null, "id": "gtv3ht2wf1rj00ckh0083jez2m", "input": { "prompt": "portrait photo of QSO dog", "hf_lora": "https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 33780\nPrompt: portrait photo of QSO dog\ntxt2img mode\nDownloading LoRA weights from - Replicate URL: https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar\nEnsuring enough disk space...\nDownloading weights: https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar\n2024-12-02T15:32:25Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/e325e995b1466ff7 url=https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar\n2024-12-02T15:32:26Z | INFO | [ Complete ] dest=/src/weights-cache/e325e995b1466ff7 size=\"9.4 MB\" total_elapsed=1.089s url=https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar\nb''\nDownloaded weights in 1.1089200973510742 seconds\nLoading LoRA took: 1.38 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:13, 1.99it/s]\n 7%|▋ | 2/28 [00:00<00:11, 2.35it/s]\n 11%|█ | 3/28 [00:01<00:11, 2.17it/s]\n 14%|█▍ | 4/28 [00:01<00:11, 2.10it/s]\n 18%|█▊ | 5/28 [00:02<00:11, 2.06it/s]\n 21%|██▏ | 6/28 [00:02<00:10, 2.03it/s]\n 25%|██▌ | 7/28 [00:03<00:10, 2.02it/s]\n 29%|██▊ | 8/28 [00:03<00:09, 2.01it/s]\n 32%|███▏ | 9/28 [00:04<00:09, 2.00it/s]\n 36%|███▌ | 10/28 [00:04<00:09, 2.00it/s]\n 39%|███▉ | 11/28 [00:05<00:08, 1.99it/s]\n 43%|████▎ | 12/28 [00:05<00:08, 1.99it/s]\n 46%|████▋ | 13/28 [00:06<00:07, 1.99it/s]\n 50%|█████ | 14/28 [00:06<00:07, 1.99it/s]\n 54%|█████▎ | 15/28 [00:07<00:06, 1.99it/s]\n 57%|█████▋ | 16/28 [00:07<00:06, 1.99it/s]\n 61%|██████ | 17/28 [00:08<00:05, 1.99it/s]\n 64%|██████▍ | 18/28 [00:08<00:05, 1.99it/s]\n 68%|██████▊ | 19/28 [00:09<00:04, 1.99it/s]\n 71%|███████▏ | 20/28 [00:09<00:04, 1.99it/s]\n 75%|███████▌ | 21/28 [00:10<00:03, 1.99it/s]\n 79%|███████▊ | 22/28 [00:10<00:03, 1.99it/s]\n 82%|████████▏ | 23/28 [00:11<00:02, 1.99it/s]\n 86%|████████▌ | 24/28 [00:11<00:02, 1.99it/s]\n 89%|████████▉ | 25/28 [00:12<00:01, 1.99it/s]\n 93%|█████████▎| 26/28 [00:12<00:01, 1.99it/s]\n 96%|█████████▋| 27/28 [00:13<00:00, 1.99it/s]\n100%|██████████| 28/28 [00:13<00:00, 1.98it/s]\n100%|██████████| 28/28 [00:13<00:00, 2.01it/s]", "metrics": { "predict_time": 15.842890662, "total_time": 15.850704 }, "output": [ "https://replicate.delivery/yhqm/er51TkhUWAyBCidCfgPmOdQfNSk6NhiyWnaCee0HWzXJjC3eE/out-0.webp" ], "started_at": "2024-12-02T15:32:25.343813Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-v4wlcregxpjtlnshblkirxl5ibm7mhdwq5ns26e3en2mlgf6h2iq", "get": "https://api.replicate.com/v1/predictions/gtv3ht2wf1rj00ckh0083jez2m", "cancel": "https://api.replicate.com/v1/predictions/gtv3ht2wf1rj00ckh0083jez2m/cancel" }, "version": "091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3" }Generated inUsing seed: 33780 Prompt: portrait photo of QSO dog txt2img mode Downloading LoRA weights from - Replicate URL: https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar Ensuring enough disk space... Downloading weights: https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar 2024-12-02T15:32:25Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/e325e995b1466ff7 url=https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar 2024-12-02T15:32:26Z | INFO | [ Complete ] dest=/src/weights-cache/e325e995b1466ff7 size="9.4 MB" total_elapsed=1.089s url=https://replicate.delivery/yhqm/DnoVJxiDrezdDCqw3LLtIQf47Gy3V8TqZNg5KxuPEcBAYdlTA/trained_model.tar b'' Downloaded weights in 1.1089200973510742 seconds Loading LoRA took: 1.38 seconds 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:13, 1.99it/s] 7%|▋ | 2/28 [00:00<00:11, 2.35it/s] 11%|█ | 3/28 [00:01<00:11, 2.17it/s] 14%|█▍ | 4/28 [00:01<00:11, 2.10it/s] 18%|█▊ | 5/28 [00:02<00:11, 2.06it/s] 21%|██▏ | 6/28 [00:02<00:10, 2.03it/s] 25%|██▌ | 7/28 [00:03<00:10, 2.02it/s] 29%|██▊ | 8/28 [00:03<00:09, 2.01it/s] 32%|███▏ | 9/28 [00:04<00:09, 2.00it/s] 36%|███▌ | 10/28 [00:04<00:09, 2.00it/s] 39%|███▉ | 11/28 [00:05<00:08, 1.99it/s] 43%|████▎ | 12/28 [00:05<00:08, 1.99it/s] 46%|████▋ | 13/28 [00:06<00:07, 1.99it/s] 50%|█████ | 14/28 [00:06<00:07, 1.99it/s] 54%|█████▎ | 15/28 [00:07<00:06, 1.99it/s] 57%|█████▋ | 16/28 [00:07<00:06, 1.99it/s] 61%|██████ | 17/28 [00:08<00:05, 1.99it/s] 64%|██████▍ | 18/28 [00:08<00:05, 1.99it/s] 68%|██████▊ | 19/28 [00:09<00:04, 1.99it/s] 71%|███████▏ | 20/28 [00:09<00:04, 1.99it/s] 75%|███████▌ | 21/28 [00:10<00:03, 1.99it/s] 79%|███████▊ | 22/28 [00:10<00:03, 1.99it/s] 82%|████████▏ | 23/28 [00:11<00:02, 1.99it/s] 86%|████████▌ | 24/28 [00:11<00:02, 1.99it/s] 89%|████████▉ | 25/28 [00:12<00:01, 1.99it/s] 93%|█████████▎| 26/28 [00:12<00:01, 1.99it/s] 96%|█████████▋| 27/28 [00:13<00:00, 1.99it/s] 100%|██████████| 28/28 [00:13<00:00, 1.98it/s] 100%|██████████| 28/28 [00:13<00:00, 2.01it/s]Prediction
lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3IDmcvttvssyhrj60ckh019jr4pqwStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- prompt
- pnt style Illustration of a latina woman
- hf_lora
- https://civitai.com/api/download/models/735262?type=Model&format=SafeTensor
- lora_scale
- 0.8
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "pnt style Illustration of a latina woman", "hf_lora": "https://civitai.com/api/download/models/735262?type=Model&format=SafeTensor", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", { input: { prompt: "pnt style Illustration of a latina woman", hf_lora: "https://civitai.com/api/download/models/735262?type=Model&format=SafeTensor", lora_scale: 0.8, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input={ "prompt": "pnt style Illustration of a latina woman", "hf_lora": "https://civitai.com/api/download/models/735262?type=Model&format=SafeTensor", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "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 lucataco/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 $'{ "version": "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", "input": { "prompt": "pnt style Illustration of a latina woman", "hf_lora": "https://civitai.com/api/download/models/735262?type=Model&format=SafeTensor", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-02T15:34:46.189119Z", "created_at": "2024-12-02T15:34:27.572000Z", "data_removed": false, "error": null, "id": "mcvttvssyhrj60ckh019jr4pqw", "input": { "prompt": "pnt style Illustration of a latina woman", "hf_lora": "https://civitai.com/api/download/models/735262?type=Model&format=SafeTensor", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 12028\nPrompt: pnt style Illustration of a latina woman\ntxt2img mode\nLoading LoRA took: 0.00 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:17, 1.52it/s]\n 7%|▋ | 2/28 [00:01<00:15, 1.70it/s]\n 11%|█ | 3/28 [00:01<00:15, 1.63it/s]\n 14%|█▍ | 4/28 [00:02<00:15, 1.59it/s]\n 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s]\n 21%|██▏ | 6/28 [00:03<00:14, 1.57it/s]\n 25%|██▌ | 7/28 [00:04<00:13, 1.56it/s]\n 29%|██▊ | 8/28 [00:05<00:12, 1.55it/s]\n 32%|███▏ | 9/28 [00:05<00:12, 1.55it/s]\n 36%|███▌ | 10/28 [00:06<00:11, 1.55it/s]\n 39%|███▉ | 11/28 [00:07<00:10, 1.55it/s]\n 43%|████▎ | 12/28 [00:07<00:10, 1.55it/s]\n 46%|████▋ | 13/28 [00:08<00:09, 1.55it/s]\n 50%|█████ | 14/28 [00:08<00:09, 1.54it/s]\n 54%|█████▎ | 15/28 [00:09<00:08, 1.54it/s]\n 57%|█████▋ | 16/28 [00:10<00:07, 1.54it/s]\n 61%|██████ | 17/28 [00:10<00:07, 1.54it/s]\n 64%|██████▍ | 18/28 [00:11<00:06, 1.54it/s]\n 68%|██████▊ | 19/28 [00:12<00:05, 1.54it/s]\n 71%|███████▏ | 20/28 [00:12<00:05, 1.54it/s]\n 75%|███████▌ | 21/28 [00:13<00:04, 1.54it/s]\n 79%|███████▊ | 22/28 [00:14<00:03, 1.54it/s]\n 82%|████████▏ | 23/28 [00:14<00:03, 1.54it/s]\n 86%|████████▌ | 24/28 [00:15<00:02, 1.54it/s]\n 89%|████████▉ | 25/28 [00:16<00:01, 1.54it/s]\n 93%|█████████▎| 26/28 [00:16<00:01, 1.54it/s]\n 96%|█████████▋| 27/28 [00:17<00:00, 1.54it/s]\n100%|██████████| 28/28 [00:18<00:00, 1.54it/s]\n100%|██████████| 28/28 [00:18<00:00, 1.55it/s]", "metrics": { "predict_time": 18.599433157, "total_time": 18.617119 }, "output": [ "https://replicate.delivery/yhqm/el3JpoTh8kyMCCnMFqVq3F2oOyUe8zqUoAT0PIEfQ0faZhbPB/out-0.webp" ], "started_at": "2024-12-02T15:34:27.589685Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-jvf3v7bploqjrgfxotbfbooqd52zh2p7jgbf6x5guwmhvm6ncyka", "get": "https://api.replicate.com/v1/predictions/mcvttvssyhrj60ckh019jr4pqw", "cancel": "https://api.replicate.com/v1/predictions/mcvttvssyhrj60ckh019jr4pqw/cancel" }, "version": "091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3" }Generated inUsing seed: 12028 Prompt: pnt style Illustration of a latina woman txt2img mode Loading LoRA took: 0.00 seconds 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:17, 1.52it/s] 7%|▋ | 2/28 [00:01<00:15, 1.70it/s] 11%|█ | 3/28 [00:01<00:15, 1.63it/s] 14%|█▍ | 4/28 [00:02<00:15, 1.59it/s] 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s] 21%|██▏ | 6/28 [00:03<00:14, 1.57it/s] 25%|██▌ | 7/28 [00:04<00:13, 1.56it/s] 29%|██▊ | 8/28 [00:05<00:12, 1.55it/s] 32%|███▏ | 9/28 [00:05<00:12, 1.55it/s] 36%|███▌ | 10/28 [00:06<00:11, 1.55it/s] 39%|███▉ | 11/28 [00:07<00:10, 1.55it/s] 43%|████▎ | 12/28 [00:07<00:10, 1.55it/s] 46%|████▋ | 13/28 [00:08<00:09, 1.55it/s] 50%|█████ | 14/28 [00:08<00:09, 1.54it/s] 54%|█████▎ | 15/28 [00:09<00:08, 1.54it/s] 57%|█████▋ | 16/28 [00:10<00:07, 1.54it/s] 61%|██████ | 17/28 [00:10<00:07, 1.54it/s] 64%|██████▍ | 18/28 [00:11<00:06, 1.54it/s] 68%|██████▊ | 19/28 [00:12<00:05, 1.54it/s] 71%|███████▏ | 20/28 [00:12<00:05, 1.54it/s] 75%|███████▌ | 21/28 [00:13<00:04, 1.54it/s] 79%|███████▊ | 22/28 [00:14<00:03, 1.54it/s] 82%|████████▏ | 23/28 [00:14<00:03, 1.54it/s] 86%|████████▌ | 24/28 [00:15<00:02, 1.54it/s] 89%|████████▉ | 25/28 [00:16<00:01, 1.54it/s] 93%|█████████▎| 26/28 [00:16<00:01, 1.54it/s] 96%|█████████▋| 27/28 [00:17<00:00, 1.54it/s] 100%|██████████| 28/28 [00:18<00:00, 1.54it/s] 100%|██████████| 28/28 [00:18<00:00, 1.55it/s]Prediction
lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3ID4kbqdyrw49rj40ckh02bxzxap8StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- prompt
- a boat in the style of TOK
- hf_lora
- lucataco/ReplicateFluxLoRA
- lora_scale
- 0.8
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "a boat in the style of TOK", "hf_lora": "lucataco/ReplicateFluxLoRA", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", { input: { prompt: "a boat in the style of TOK", hf_lora: "lucataco/ReplicateFluxLoRA", lora_scale: 0.8, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input={ "prompt": "a boat in the style of TOK", "hf_lora": "lucataco/ReplicateFluxLoRA", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "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 lucataco/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 $'{ "version": "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", "input": { "prompt": "a boat in the style of TOK", "hf_lora": "lucataco/ReplicateFluxLoRA", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-02T15:36:57.368102Z", "created_at": "2024-12-02T15:36:31.010000Z", "data_removed": false, "error": null, "id": "4kbqdyrw49rj40ckh02bxzxap8", "input": { "prompt": "a boat in the style of TOK", "hf_lora": "lucataco/ReplicateFluxLoRA", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 7974\nPrompt: a boat in the style of TOK\ntxt2img mode\nDownloading LoRA weights from - HF path: lucataco/ReplicateFluxLoRA\nLoading LoRA took: 0.97 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:17, 1.53it/s]\n 7%|▋ | 2/28 [00:01<00:15, 1.70it/s]\n 11%|█ | 3/28 [00:01<00:15, 1.63it/s]\n 14%|█▍ | 4/28 [00:02<00:15, 1.60it/s]\n 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s]\n 21%|██▏ | 6/28 [00:03<00:13, 1.57it/s]\n 25%|██▌ | 7/28 [00:04<00:13, 1.57it/s]\n 29%|██▊ | 8/28 [00:05<00:12, 1.56it/s]\n 32%|███▏ | 9/28 [00:05<00:12, 1.56it/s]\n 36%|███▌ | 10/28 [00:06<00:11, 1.56it/s]\n 39%|███▉ | 11/28 [00:06<00:10, 1.56it/s]\n 43%|████▎ | 12/28 [00:07<00:10, 1.56it/s]\n 46%|████▋ | 13/28 [00:08<00:09, 1.56it/s]\n 50%|█████ | 14/28 [00:08<00:09, 1.55it/s]\n 54%|█████▎ | 15/28 [00:09<00:08, 1.55it/s]\n 57%|█████▋ | 16/28 [00:10<00:07, 1.55it/s]\n 61%|██████ | 17/28 [00:10<00:07, 1.55it/s]\n 64%|██████▍ | 18/28 [00:11<00:06, 1.55it/s]\n 68%|██████▊ | 19/28 [00:12<00:05, 1.55it/s]\n 71%|███████▏ | 20/28 [00:12<00:05, 1.55it/s]\n 75%|███████▌ | 21/28 [00:13<00:04, 1.55it/s]\n 79%|███████▊ | 22/28 [00:14<00:03, 1.55it/s]\n 82%|████████▏ | 23/28 [00:14<00:03, 1.55it/s]\n 86%|████████▌ | 24/28 [00:15<00:02, 1.55it/s]\n 89%|████████▉ | 25/28 [00:16<00:01, 1.55it/s]\n 93%|█████████▎| 26/28 [00:16<00:01, 1.55it/s]\n 96%|█████████▋| 27/28 [00:17<00:00, 1.55it/s]\n100%|██████████| 28/28 [00:17<00:00, 1.55it/s]\n100%|██████████| 28/28 [00:17<00:00, 1.56it/s]", "metrics": { "predict_time": 19.435561314, "total_time": 26.358102 }, "output": [ "https://replicate.delivery/yhqm/WQiGaRglpC7XF9xk46hvcH8kScXUfNhf8XqfV49xUncywwtnA/out-0.webp" ], "started_at": "2024-12-02T15:36:37.932540Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-tsfvoqvjhcp4eh6pigkdl6wnetva4hywaajxxzajqitanknja4xa", "get": "https://api.replicate.com/v1/predictions/4kbqdyrw49rj40ckh02bxzxap8", "cancel": "https://api.replicate.com/v1/predictions/4kbqdyrw49rj40ckh02bxzxap8/cancel" }, "version": "091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3" }Generated inUsing seed: 7974 Prompt: a boat in the style of TOK txt2img mode Downloading LoRA weights from - HF path: lucataco/ReplicateFluxLoRA Loading LoRA took: 0.97 seconds 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:17, 1.53it/s] 7%|▋ | 2/28 [00:01<00:15, 1.70it/s] 11%|█ | 3/28 [00:01<00:15, 1.63it/s] 14%|█▍ | 4/28 [00:02<00:15, 1.60it/s] 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s] 21%|██▏ | 6/28 [00:03<00:13, 1.57it/s] 25%|██▌ | 7/28 [00:04<00:13, 1.57it/s] 29%|██▊ | 8/28 [00:05<00:12, 1.56it/s] 32%|███▏ | 9/28 [00:05<00:12, 1.56it/s] 36%|███▌ | 10/28 [00:06<00:11, 1.56it/s] 39%|███▉ | 11/28 [00:06<00:10, 1.56it/s] 43%|████▎ | 12/28 [00:07<00:10, 1.56it/s] 46%|████▋ | 13/28 [00:08<00:09, 1.56it/s] 50%|█████ | 14/28 [00:08<00:09, 1.55it/s] 54%|█████▎ | 15/28 [00:09<00:08, 1.55it/s] 57%|█████▋ | 16/28 [00:10<00:07, 1.55it/s] 61%|██████ | 17/28 [00:10<00:07, 1.55it/s] 64%|██████▍ | 18/28 [00:11<00:06, 1.55it/s] 68%|██████▊ | 19/28 [00:12<00:05, 1.55it/s] 71%|███████▏ | 20/28 [00:12<00:05, 1.55it/s] 75%|███████▌ | 21/28 [00:13<00:04, 1.55it/s] 79%|███████▊ | 22/28 [00:14<00:03, 1.55it/s] 82%|████████▏ | 23/28 [00:14<00:03, 1.55it/s] 86%|████████▌ | 24/28 [00:15<00:02, 1.55it/s] 89%|████████▉ | 25/28 [00:16<00:01, 1.55it/s] 93%|█████████▎| 26/28 [00:16<00:01, 1.55it/s] 96%|█████████▋| 27/28 [00:17<00:00, 1.55it/s] 100%|██████████| 28/28 [00:17<00:00, 1.55it/s] 100%|██████████| 28/28 [00:17<00:00, 1.56it/s]Prediction
lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3IDkbkq3pe5bsrj40ckh02943cjv0StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- prompt
- A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll
- hf_lora
- davisbro/half_illustration
- lora_scale
- 0.8
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "hf_lora": "davisbro/half_illustration", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", { input: { prompt: "A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", hf_lora: "davisbro/half_illustration", lora_scale: 0.8, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input={ "prompt": "A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "hf_lora": "davisbro/half_illustration", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "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 lucataco/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 $'{ "version": "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", "input": { "prompt": "A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "hf_lora": "davisbro/half_illustration", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-02T15:37:40.228649Z", "created_at": "2024-12-02T15:37:14.334000Z", "data_removed": false, "error": null, "id": "kbkq3pe5bsrj40ckh02943cjv0", "input": { "prompt": "A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll", "hf_lora": "davisbro/half_illustration", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 62365\nPrompt: A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll\ntxt2img mode\nDownloading LoRA weights from - HF path: davisbro/half_illustration\nLoading LoRA took: 0.81 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:17, 1.52it/s]\n 7%|▋ | 2/28 [00:01<00:15, 1.70it/s]\n 11%|█ | 3/28 [00:01<00:15, 1.62it/s]\n 14%|█▍ | 4/28 [00:02<00:15, 1.58it/s]\n 18%|█▊ | 5/28 [00:03<00:14, 1.57it/s]\n 21%|██▏ | 6/28 [00:03<00:14, 1.56it/s]\n 25%|██▌ | 7/28 [00:04<00:13, 1.55it/s]\n 29%|██▊ | 8/28 [00:05<00:12, 1.54it/s]\n 32%|███▏ | 9/28 [00:05<00:12, 1.54it/s]\n 36%|███▌ | 10/28 [00:06<00:11, 1.54it/s]\n 39%|███▉ | 11/28 [00:07<00:11, 1.54it/s]\n 43%|████▎ | 12/28 [00:07<00:10, 1.54it/s]\n 46%|████▋ | 13/28 [00:08<00:09, 1.54it/s]\n 50%|█████ | 14/28 [00:09<00:09, 1.53it/s]\n 54%|█████▎ | 15/28 [00:09<00:08, 1.53it/s]\n 57%|█████▋ | 16/28 [00:10<00:07, 1.53it/s]\n 61%|██████ | 17/28 [00:10<00:07, 1.53it/s]\n 64%|██████▍ | 18/28 [00:11<00:06, 1.53it/s]\n 68%|██████▊ | 19/28 [00:12<00:05, 1.53it/s]\n 71%|███████▏ | 20/28 [00:12<00:05, 1.53it/s]\n 75%|███████▌ | 21/28 [00:13<00:04, 1.53it/s]\n 79%|███████▊ | 22/28 [00:14<00:03, 1.53it/s]\n 82%|████████▏ | 23/28 [00:14<00:03, 1.53it/s]\n 86%|████████▌ | 24/28 [00:15<00:02, 1.53it/s]\n 89%|████████▉ | 25/28 [00:16<00:01, 1.53it/s]\n 93%|█████████▎| 26/28 [00:16<00:01, 1.53it/s]\n 96%|█████████▋| 27/28 [00:17<00:00, 1.53it/s]\n100%|██████████| 28/28 [00:18<00:00, 1.53it/s]\n100%|██████████| 28/28 [00:18<00:00, 1.54it/s]", "metrics": { "predict_time": 19.482127467, "total_time": 25.894649 }, "output": [ "https://replicate.delivery/yhqm/DeyjLXef75Vpgop5YHXs9Ac4oNiLrsjhOcXAyw8iiK0JywtnA/out-0.webp" ], "started_at": "2024-12-02T15:37:20.746522Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-iwrzofj4kr4uwmor5hyyb3llzcdkpmht4jymqqkppnodddvtycca", "get": "https://api.replicate.com/v1/predictions/kbkq3pe5bsrj40ckh02943cjv0", "cancel": "https://api.replicate.com/v1/predictions/kbkq3pe5bsrj40ckh02943cjv0/cancel" }, "version": "091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3" }Generated inUsing seed: 62365 Prompt: A photo, editorial avant-garde dramatic action pose of a white person wearing 60s round wacky sunglasses with gemstones hanging pulling glasses down looking forward, in Italy at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll txt2img mode Downloading LoRA weights from - HF path: davisbro/half_illustration Loading LoRA took: 0.81 seconds 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:17, 1.52it/s] 7%|▋ | 2/28 [00:01<00:15, 1.70it/s] 11%|█ | 3/28 [00:01<00:15, 1.62it/s] 14%|█▍ | 4/28 [00:02<00:15, 1.58it/s] 18%|█▊ | 5/28 [00:03<00:14, 1.57it/s] 21%|██▏ | 6/28 [00:03<00:14, 1.56it/s] 25%|██▌ | 7/28 [00:04<00:13, 1.55it/s] 29%|██▊ | 8/28 [00:05<00:12, 1.54it/s] 32%|███▏ | 9/28 [00:05<00:12, 1.54it/s] 36%|███▌ | 10/28 [00:06<00:11, 1.54it/s] 39%|███▉ | 11/28 [00:07<00:11, 1.54it/s] 43%|████▎ | 12/28 [00:07<00:10, 1.54it/s] 46%|████▋ | 13/28 [00:08<00:09, 1.54it/s] 50%|█████ | 14/28 [00:09<00:09, 1.53it/s] 54%|█████▎ | 15/28 [00:09<00:08, 1.53it/s] 57%|█████▋ | 16/28 [00:10<00:07, 1.53it/s] 61%|██████ | 17/28 [00:10<00:07, 1.53it/s] 64%|██████▍ | 18/28 [00:11<00:06, 1.53it/s] 68%|██████▊ | 19/28 [00:12<00:05, 1.53it/s] 71%|███████▏ | 20/28 [00:12<00:05, 1.53it/s] 75%|███████▌ | 21/28 [00:13<00:04, 1.53it/s] 79%|███████▊ | 22/28 [00:14<00:03, 1.53it/s] 82%|████████▏ | 23/28 [00:14<00:03, 1.53it/s] 86%|████████▌ | 24/28 [00:15<00:02, 1.53it/s] 89%|████████▉ | 25/28 [00:16<00:01, 1.53it/s] 93%|█████████▎| 26/28 [00:16<00:01, 1.53it/s] 96%|█████████▋| 27/28 [00:17<00:00, 1.53it/s] 100%|██████████| 28/28 [00:18<00:00, 1.53it/s] 100%|██████████| 28/28 [00:18<00:00, 1.54it/s]Prediction
lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3IDhy2bvxy0nhrj00ckh04r4npd54StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- prompt
- portrait photo of TOK with purple hair
- hf_lora
- https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar
- lora_scale
- 0.8
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- prompt_strength
- 0.8
- num_inference_steps
- 28
{ "prompt": "portrait photo of TOK with purple hair", "hf_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", { input: { prompt: "portrait photo of TOK with purple hair", hf_lora: "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", lora_scale: 0.8, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, prompt_strength: 0.8, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-dev-lora using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input={ "prompt": "portrait photo of TOK with purple hair", "hf_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "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 lucataco/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 $'{ "version": "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", "input": { "prompt": "portrait photo of TOK with purple hair", "hf_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-12-02T15:42:59.301185Z", "created_at": "2024-12-02T15:42:40.812000Z", "data_removed": false, "error": null, "id": "hy2bvxy0nhrj00ckh04r4npd54", "input": { "prompt": "portrait photo of TOK with purple hair", "hf_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 0.8, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "prompt_strength": 0.8, "num_inference_steps": 28 }, "logs": "Using seed: 46453\nPrompt: portrait photo of TOK with purple hair\ntxt2img mode\nLoading LoRA took: 0.00 seconds\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:17, 1.53it/s]\n 7%|▋ | 2/28 [00:01<00:15, 1.71it/s]\n 11%|█ | 3/28 [00:01<00:15, 1.63it/s]\n 14%|█▍ | 4/28 [00:02<00:14, 1.60it/s]\n 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s]\n 21%|██▏ | 6/28 [00:03<00:13, 1.57it/s]\n 25%|██▌ | 7/28 [00:04<00:13, 1.56it/s]\n 29%|██▊ | 8/28 [00:05<00:12, 1.56it/s]\n 32%|███▏ | 9/28 [00:05<00:12, 1.56it/s]\n 36%|███▌ | 10/28 [00:06<00:11, 1.55it/s]\n 39%|███▉ | 11/28 [00:06<00:10, 1.55it/s]\n 43%|████▎ | 12/28 [00:07<00:10, 1.55it/s]\n 46%|████▋ | 13/28 [00:08<00:09, 1.55it/s]\n 50%|█████ | 14/28 [00:08<00:09, 1.55it/s]\n 54%|█████▎ | 15/28 [00:09<00:08, 1.55it/s]\n 57%|█████▋ | 16/28 [00:10<00:07, 1.55it/s]\n 61%|██████ | 17/28 [00:10<00:07, 1.55it/s]\n 64%|██████▍ | 18/28 [00:11<00:06, 1.55it/s]\n 68%|██████▊ | 19/28 [00:12<00:05, 1.55it/s]\n 71%|███████▏ | 20/28 [00:12<00:05, 1.55it/s]\n 75%|███████▌ | 21/28 [00:13<00:04, 1.55it/s]\n 79%|███████▊ | 22/28 [00:14<00:03, 1.55it/s]\n 82%|████████▏ | 23/28 [00:14<00:03, 1.55it/s]\n 86%|████████▌ | 24/28 [00:15<00:02, 1.55it/s]\n 89%|████████▉ | 25/28 [00:16<00:01, 1.55it/s]\n 93%|█████████▎| 26/28 [00:16<00:01, 1.55it/s]\n 96%|█████████▋| 27/28 [00:17<00:00, 1.55it/s]\n100%|██████████| 28/28 [00:17<00:00, 1.55it/s]\n100%|██████████| 28/28 [00:17<00:00, 1.56it/s]", "metrics": { "predict_time": 18.480079272, "total_time": 18.489185 }, "output": [ "https://replicate.delivery/yhqm/jnk4vMe0ptyjGKPzYkeJT3cdIFBiRSTpveampSCUfyAM4hbPB/out-0.webp" ], "started_at": "2024-12-02T15:42:40.821105Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/qoxq-vvtxjgfd7tmhgml2p6rqysjy5b35q46p62w4dy5u6h3vlj7eexta", "get": "https://api.replicate.com/v1/predictions/hy2bvxy0nhrj00ckh04r4npd54", "cancel": "https://api.replicate.com/v1/predictions/hy2bvxy0nhrj00ckh04r4npd54/cancel" }, "version": "091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3" }Generated inUsing seed: 46453 Prompt: portrait photo of TOK with purple hair txt2img mode Loading LoRA took: 0.00 seconds 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:17, 1.53it/s] 7%|▋ | 2/28 [00:01<00:15, 1.71it/s] 11%|█ | 3/28 [00:01<00:15, 1.63it/s] 14%|█▍ | 4/28 [00:02<00:14, 1.60it/s] 18%|█▊ | 5/28 [00:03<00:14, 1.58it/s] 21%|██▏ | 6/28 [00:03<00:13, 1.57it/s] 25%|██▌ | 7/28 [00:04<00:13, 1.56it/s] 29%|██▊ | 8/28 [00:05<00:12, 1.56it/s] 32%|███▏ | 9/28 [00:05<00:12, 1.56it/s] 36%|███▌ | 10/28 [00:06<00:11, 1.55it/s] 39%|███▉ | 11/28 [00:06<00:10, 1.55it/s] 43%|████▎ | 12/28 [00:07<00:10, 1.55it/s] 46%|████▋ | 13/28 [00:08<00:09, 1.55it/s] 50%|█████ | 14/28 [00:08<00:09, 1.55it/s] 54%|█████▎ | 15/28 [00:09<00:08, 1.55it/s] 57%|█████▋ | 16/28 [00:10<00:07, 1.55it/s] 61%|██████ | 17/28 [00:10<00:07, 1.55it/s] 64%|██████▍ | 18/28 [00:11<00:06, 1.55it/s] 68%|██████▊ | 19/28 [00:12<00:05, 1.55it/s] 71%|███████▏ | 20/28 [00:12<00:05, 1.55it/s] 75%|███████▌ | 21/28 [00:13<00:04, 1.55it/s] 79%|███████▊ | 22/28 [00:14<00:03, 1.55it/s] 82%|████████▏ | 23/28 [00:14<00:03, 1.55it/s] 86%|████████▌ | 24/28 [00:15<00:02, 1.55it/s] 89%|████████▉ | 25/28 [00:16<00:01, 1.55it/s] 93%|█████████▎| 26/28 [00:16<00:01, 1.55it/s] 96%|█████████▋| 27/28 [00:17<00:00, 1.55it/s] 100%|██████████| 28/28 [00:17<00:00, 1.55it/s] 100%|██████████| 28/28 [00:17<00:00, 1.56it/s]
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