lucataco / flux-time100
Flux finetune of the style: TIMES 100 Most Influential People in AI (Updated 9 months, 1 week ago)
- Public
- 653 runs
Prediction
lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501ID3hbkrzr111rm20chvkbs9d1a7rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:4
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", { input: { model: "dev", prompt: "portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:4", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", input={ "model": "dev", "prompt": "portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/flux-time100 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-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", "input": { "model": "dev", "prompt": "portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-10T16:50:22.740324Z", "created_at": "2024-09-10T16:49:23.720000Z", "data_removed": false, "error": null, "id": "3hbkrzr111rm20chvkbs9d1a7r", "input": { "model": "dev", "prompt": "portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 32829\nPrompt: portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background\n[!] txt2img mode\nUsing dev model\nfree=7834787991552\nDownloading weights\n2024-09-10T16:49:54Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpyxd5o72a/weights url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar\n2024-09-10T16:49:56Z | INFO | [ Complete ] dest=/tmp/tmpyxd5o72a/weights size=\"172 MB\" total_elapsed=2.047s url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar\nDownloaded weights in 2.08s\nLoaded LoRAs in 20.09s\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, 4.24it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.00it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.90it/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, 3.77it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.77it/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<00:03, 3.76it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.76it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.76it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.76it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.76it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.76it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.76it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.76it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.76it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.76it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.76it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.76it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.76it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.76it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.76it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.76it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.78it/s]", "metrics": { "predict_time": 28.492371015, "total_time": 59.020324 }, "output": [ "https://replicate.delivery/yhqm/nwqDoLRusPZvMNxxs9frtGUoiuL47CcWpqDkrleRcL5OribTA/out-0.webp" ], "started_at": "2024-09-10T16:49:54.247953Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3hbkrzr111rm20chvkbs9d1a7r", "cancel": "https://api.replicate.com/v1/predictions/3hbkrzr111rm20chvkbs9d1a7r/cancel" }, "version": "99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501" }Generated inUsing seed: 32829 Prompt: portrait of a handsome latino man in grayscale in a suit, in the style of TMHNDRD blue glow on a white background [!] txt2img mode Using dev model free=7834787991552 Downloading weights 2024-09-10T16:49:54Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpyxd5o72a/weights url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar 2024-09-10T16:49:56Z | INFO | [ Complete ] dest=/tmp/tmpyxd5o72a/weights size="172 MB" total_elapsed=2.047s url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar Downloaded weights in 2.08s Loaded LoRAs in 20.09s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.75it/s] 7%|▋ | 2/28 [00:00<00:06, 4.24it/s] 11%|█ | 3/28 [00:00<00:06, 4.00it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.90it/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, 3.77it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.77it/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<00:03, 3.76it/s] 50%|█████ | 14/28 [00:03<00:03, 3.76it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.76it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.76it/s] 61%|██████ | 17/28 [00:04<00:02, 3.76it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.76it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.76it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.76it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.76it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.76it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.76it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.76it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.76it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.76it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.76it/s] 100%|██████████| 28/28 [00:07<00:00, 3.76it/s] 100%|██████████| 28/28 [00:07<00:00, 3.78it/s]Prediction
lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501IDnb179js7f5rm40chvms82z57nmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background
- extra_lora
- https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:4
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background", "extra_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", { input: { model: "dev", prompt: "portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background", extra_lora: "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:4", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", input={ "model": "dev", "prompt": "portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background", "extra_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/flux-time100 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-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", "input": { "model": "dev", "prompt": "portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background", "extra_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-10T18:29:32.686023Z", "created_at": "2024-09-10T18:28:57.337000Z", "data_removed": false, "error": null, "id": "nb179js7f5rm40chvms82z57nm", "input": { "model": "dev", "prompt": "portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background", "extra_lora": "https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 4999\nPrompt: portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background\n[!] txt2img mode\nUsing dev model\nLoading extra LoRA weights from: https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar\nfree=7977871036416\nDownloading weights\n2024-09-10T18:29:03Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk_67pleu/weights url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar\n2024-09-10T18:29:04Z | INFO | [ Complete ] dest=/tmp/tmpk_67pleu/weights size=\"172 MB\" total_elapsed=1.300s url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar\nDownloaded weights in 1.33s\nfree=7977698979840\nDownloading weights\n2024-09-10T18:29:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpeub908x_/weights url=https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar\n2024-09-10T18:29:13Z | INFO | [ Complete ] dest=/tmp/tmpeub908x_/weights size=\"172 MB\" total_elapsed=1.850s url=https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar\nDownloaded weights in 1.94s\nLoaded LoRAs in 19.44s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:01<00:33, 1.26s/it]\n 7%|▋ | 2/28 [00:01<00:17, 1.49it/s]\n 11%|█ | 3/28 [00:01<00:12, 1.98it/s]\n 14%|█▍ | 4/28 [00:02<00:10, 2.35it/s]\n 18%|█▊ | 5/28 [00:02<00:08, 2.61it/s]\n 21%|██▏ | 6/28 [00:02<00:07, 2.80it/s]\n 25%|██▌ | 7/28 [00:03<00:07, 2.94it/s]\n 29%|██▊ | 8/28 [00:03<00:06, 3.04it/s]\n 32%|███▏ | 9/28 [00:03<00:06, 3.10it/s]\n 36%|███▌ | 10/28 [00:03<00:05, 3.15it/s]\n 39%|███▉ | 11/28 [00:04<00:05, 3.19it/s]\n 43%|████▎ | 12/28 [00:04<00:04, 3.21it/s]\n 46%|████▋ | 13/28 [00:04<00:04, 3.23it/s]\n 50%|█████ | 14/28 [00:05<00:04, 3.24it/s]\n 54%|█████▎ | 15/28 [00:05<00:04, 3.25it/s]\n 57%|█████▋ | 16/28 [00:05<00:03, 3.25it/s]\n 61%|██████ | 17/28 [00:06<00:03, 3.25it/s]\n 64%|██████▍ | 18/28 [00:06<00:03, 3.26it/s]\n 68%|██████▊ | 19/28 [00:06<00:02, 3.26it/s]\n 71%|███████▏ | 20/28 [00:07<00:02, 3.26it/s]\n 75%|███████▌ | 21/28 [00:07<00:02, 3.26it/s]\n 79%|███████▊ | 22/28 [00:07<00:01, 3.26it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 3.26it/s]\n 86%|████████▌ | 24/28 [00:08<00:01, 3.26it/s]\n 89%|████████▉ | 25/28 [00:08<00:00, 3.27it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 3.27it/s]\n 96%|█████████▋| 27/28 [00:09<00:00, 3.27it/s]\n100%|██████████| 28/28 [00:09<00:00, 3.27it/s]\n100%|██████████| 28/28 [00:09<00:00, 2.95it/s]", "metrics": { "predict_time": 29.469655512, "total_time": 35.349023 }, "output": [ "https://replicate.delivery/yhqm/e6qdOs47Y8V3ek0MaxcLTPjQAxjV54fz2f1DsYnlmdyzgQuNB/out-0.webp" ], "started_at": "2024-09-10T18:29:03.216367Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nb179js7f5rm40chvms82z57nm", "cancel": "https://api.replicate.com/v1/predictions/nb179js7f5rm40chvms82z57nm/cancel" }, "version": "99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501" }Generated inUsing seed: 4999 Prompt: portrait of TOK woman in grayscale, in the style of TMHNDRD with purple color on a white background [!] txt2img mode Using dev model Loading extra LoRA weights from: https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar free=7977871036416 Downloading weights 2024-09-10T18:29:03Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpk_67pleu/weights url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar 2024-09-10T18:29:04Z | INFO | [ Complete ] dest=/tmp/tmpk_67pleu/weights size="172 MB" total_elapsed=1.300s url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar Downloaded weights in 1.33s free=7977698979840 Downloading weights 2024-09-10T18:29:12Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpeub908x_/weights url=https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar 2024-09-10T18:29:13Z | INFO | [ Complete ] dest=/tmp/tmpeub908x_/weights size="172 MB" total_elapsed=1.850s url=https://replicate.delivery/yhqm/9vSmRCa8Vv7bFtKfCfXTRzTq4X71tZW0LtLCb1l49bTSo8TTA/trained_model.tar Downloaded weights in 1.94s Loaded LoRAs in 19.44s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:01<00:33, 1.26s/it] 7%|▋ | 2/28 [00:01<00:17, 1.49it/s] 11%|█ | 3/28 [00:01<00:12, 1.98it/s] 14%|█▍ | 4/28 [00:02<00:10, 2.35it/s] 18%|█▊ | 5/28 [00:02<00:08, 2.61it/s] 21%|██▏ | 6/28 [00:02<00:07, 2.80it/s] 25%|██▌ | 7/28 [00:03<00:07, 2.94it/s] 29%|██▊ | 8/28 [00:03<00:06, 3.04it/s] 32%|███▏ | 9/28 [00:03<00:06, 3.10it/s] 36%|███▌ | 10/28 [00:03<00:05, 3.15it/s] 39%|███▉ | 11/28 [00:04<00:05, 3.19it/s] 43%|████▎ | 12/28 [00:04<00:04, 3.21it/s] 46%|████▋ | 13/28 [00:04<00:04, 3.23it/s] 50%|█████ | 14/28 [00:05<00:04, 3.24it/s] 54%|█████▎ | 15/28 [00:05<00:04, 3.25it/s] 57%|█████▋ | 16/28 [00:05<00:03, 3.25it/s] 61%|██████ | 17/28 [00:06<00:03, 3.25it/s] 64%|██████▍ | 18/28 [00:06<00:03, 3.26it/s] 68%|██████▊ | 19/28 [00:06<00:02, 3.26it/s] 71%|███████▏ | 20/28 [00:07<00:02, 3.26it/s] 75%|███████▌ | 21/28 [00:07<00:02, 3.26it/s] 79%|███████▊ | 22/28 [00:07<00:01, 3.26it/s] 82%|████████▏ | 23/28 [00:07<00:01, 3.26it/s] 86%|████████▌ | 24/28 [00:08<00:01, 3.26it/s] 89%|████████▉ | 25/28 [00:08<00:00, 3.27it/s] 93%|█████████▎| 26/28 [00:08<00:00, 3.27it/s] 96%|█████████▋| 27/28 [00:09<00:00, 3.27it/s] 100%|██████████| 28/28 [00:09<00:00, 3.27it/s] 100%|██████████| 28/28 [00:09<00:00, 2.95it/s]Prediction
lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501IDmr217j3115rm20chvjkt69wyymStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:4
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", { input: { model: "dev", prompt: "portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:4", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", input={ "model": "dev", "prompt": "portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/flux-time100 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-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", "input": { "model": "dev", "prompt": "portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-10T15:57:51.995708Z", "created_at": "2024-09-10T15:57:22.569000Z", "data_removed": false, "error": null, "id": "mr217j3115rm20chvjkt69wyym", "input": { "model": "dev", "prompt": "portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 38367\nPrompt: portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 8.63s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.78it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.26it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.03it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.93it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.87it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.84it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.82it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.80it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.79it/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, 3.78it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.78it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.78it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.78it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.78it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.78it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.78it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.78it/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, 3.78it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.78it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.78it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]", "metrics": { "predict_time": 16.627380011, "total_time": 29.426708 }, "output": [ "https://replicate.delivery/yhqm/u7FQKt2fFc3iPCYkFH2TPMrlLf7upPPMbs9fEgTqNdVenHuNB/out-0.webp" ], "started_at": "2024-09-10T15:57:35.368328Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mr217j3115rm20chvjkt69wyym", "cancel": "https://api.replicate.com/v1/predictions/mr217j3115rm20chvjkt69wyym/cancel" }, "version": "99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501" }Generated inUsing seed: 38367 Prompt: portrait of a latina woman in grayscale, in the style of TMHNDRD with primary green color on a white background [!] txt2img mode Using dev model Loaded LoRAs in 8.63s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.78it/s] 7%|▋ | 2/28 [00:00<00:06, 4.26it/s] 11%|█ | 3/28 [00:00<00:06, 4.03it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.93it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.87it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.84it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.82it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.80it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.79it/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, 3.78it/s] 61%|██████ | 17/28 [00:04<00:02, 3.78it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.78it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.78it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.78it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.78it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.78it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.78it/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, 3.78it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.78it/s] 100%|██████████| 28/28 [00:07<00:00, 3.78it/s] 100%|██████████| 28/28 [00:07<00:00, 3.80it/s]Prediction
lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501IDcsr6p345wxrm00chvmtb0x32bcStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 3:4
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", { input: { model: "dev", prompt: "portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background", lora_scale: 1, num_outputs: 1, aspect_ratio: "3:4", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", input={ "model": "dev", "prompt": "portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/flux-time100 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-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", "input": { "model": "dev", "prompt": "portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-10T18:31:56.712764Z", "created_at": "2024-09-10T18:31:32.583000Z", "data_removed": false, "error": null, "id": "csr6p345wxrm00chvmtb0x32bc", "input": { "model": "dev", "prompt": "portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "3:4", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 43534\nPrompt: portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 8.86s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.78it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.27it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.03it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.93it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.87it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.84it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.82it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.81it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.80it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.80it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.79it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.79it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.79it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.79it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.79it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.79it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.79it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.79it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.78it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.79it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.78it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.79it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.78it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.79it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.79it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.78it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.79it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.79it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.81it/s]", "metrics": { "predict_time": 16.736025976, "total_time": 24.129764 }, "output": [ "https://replicate.delivery/yhqm/6eh8ehum6OmZ1U1oHHcXeA11wjzwgVaaO3qzXGmmPOh4UI3mA/out-0.webp" ], "started_at": "2024-09-10T18:31:39.976738Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/csr6p345wxrm00chvmtb0x32bc", "cancel": "https://api.replicate.com/v1/predictions/csr6p345wxrm00chvmtb0x32bc/cancel" }, "version": "99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501" }Generated inUsing seed: 43534 Prompt: portrait of a pretty latina woman in grayscale, in the style of TMHNDRD with a yellow glow on a white background [!] txt2img mode Using dev model Loaded LoRAs in 8.86s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.78it/s] 7%|▋ | 2/28 [00:00<00:06, 4.27it/s] 11%|█ | 3/28 [00:00<00:06, 4.03it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.93it/s] 18%|█▊ | 5/28 [00:01<00:05, 3.87it/s] 21%|██▏ | 6/28 [00:01<00:05, 3.84it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.82it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.81it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.80it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.80it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.79it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.79it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.79it/s] 50%|█████ | 14/28 [00:03<00:03, 3.79it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.79it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.79it/s] 61%|██████ | 17/28 [00:04<00:02, 3.79it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.79it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.78it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.79it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.78it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.79it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.78it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.79it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.79it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.78it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.79it/s] 100%|██████████| 28/28 [00:07<00:00, 3.79it/s] 100%|██████████| 28/28 [00:07<00:00, 3.81it/s]Prediction
lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501ID9mxa0xdh75rm40chtkztn0m7ewStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of a latina woman, in the style of TMHNDRD
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of a latina woman, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", { input: { model: "dev", prompt: "portrait of a latina woman, in the style of TMHNDRD", lora_scale: 1, num_outputs: 1, aspect_ratio: "4:5", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", input={ "model": "dev", "prompt": "portrait of a latina woman, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/flux-time100 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-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", "input": { "model": "dev", "prompt": "portrait of a latina woman, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-09T04:17:11.478612Z", "created_at": "2024-09-09T04:16:52.537000Z", "data_removed": false, "error": null, "id": "9mxa0xdh75rm40chtkztn0m7ew", "input": { "model": "dev", "prompt": "portrait of a latina woman, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 37630\nPrompt: portrait of a latina woman, in the style of TMHNDRD\n[!] txt2img mode\nUsing dev model\nfree=8243185717248\nDownloading weights\n2024-09-09T04:16:52Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpq373uoim/weights url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar\n2024-09-09T04:16:56Z | INFO | [ Complete ] dest=/tmp/tmpq373uoim/weights size=\"172 MB\" total_elapsed=3.570s url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar\nDownloaded weights in 3.60s\nLoaded LoRAs in 11.28s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:06, 3.95it/s]\n 7%|▋ | 2/28 [00:00<00:05, 4.46it/s]\n 11%|█ | 3/28 [00:00<00:05, 4.22it/s]\n 14%|█▍ | 4/28 [00:00<00:05, 4.11it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 4.05it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 4.02it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.99it/s]\n 29%|██▊ | 8/28 [00:01<00:05, 3.98it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.97it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.96it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.96it/s]\n 43%|████▎ | 12/28 [00:02<00:04, 3.96it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.96it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.95it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.95it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.95it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.95it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.95it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.95it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.95it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.95it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.95it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.95it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.95it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.95it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.95it/s]\n 96%|█████████▋| 27/28 [00:06<00:00, 3.95it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.95it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.98it/s]", "metrics": { "predict_time": 18.933786435000002, "total_time": 18.941612 }, "output": [ "https://replicate.delivery/yhqm/Us1HIBNINyakLVaKMPHOOIhUiq2JVJWOD9qHrGd3At6xow2E/out-0.webp" ], "started_at": "2024-09-09T04:16:52.544825Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/9mxa0xdh75rm40chtkztn0m7ew", "cancel": "https://api.replicate.com/v1/predictions/9mxa0xdh75rm40chtkztn0m7ew/cancel" }, "version": "99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501" }Generated inUsing seed: 37630 Prompt: portrait of a latina woman, in the style of TMHNDRD [!] txt2img mode Using dev model free=8243185717248 Downloading weights 2024-09-09T04:16:52Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpq373uoim/weights url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar 2024-09-09T04:16:56Z | INFO | [ Complete ] dest=/tmp/tmpq373uoim/weights size="172 MB" total_elapsed=3.570s url=https://replicate.delivery/yhqm/GQlnLt9mSqLyGZCwxDHoXrXJUpfD5fRTqZSWBFRe7bz0eJsNB/trained_model.tar Downloaded weights in 3.60s Loaded LoRAs in 11.28s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:06, 3.95it/s] 7%|▋ | 2/28 [00:00<00:05, 4.46it/s] 11%|█ | 3/28 [00:00<00:05, 4.22it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.11it/s] 18%|█▊ | 5/28 [00:01<00:05, 4.05it/s] 21%|██▏ | 6/28 [00:01<00:05, 4.02it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.99it/s] 29%|██▊ | 8/28 [00:01<00:05, 3.98it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.97it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.96it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.96it/s] 43%|████▎ | 12/28 [00:02<00:04, 3.96it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.96it/s] 50%|█████ | 14/28 [00:03<00:03, 3.95it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.95it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.95it/s] 61%|██████ | 17/28 [00:04<00:02, 3.95it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.95it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.95it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.95it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.95it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.95it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.95it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.95it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.95it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.95it/s] 96%|█████████▋| 27/28 [00:06<00:00, 3.95it/s] 100%|██████████| 28/28 [00:07<00:00, 3.95it/s] 100%|██████████| 28/28 [00:07<00:00, 3.98it/s]Prediction
lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501IDh465smfygdrm40chtm1sa4c424StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- portrait of a latino man, in the style of TMHNDRD
- lora_scale
- 1
- num_outputs
- 1
- aspect_ratio
- 4:5
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 90
- prompt_strength
- 0.8
- extra_lora_scale
- 1
- num_inference_steps
- 28
{ "model": "dev", "prompt": "portrait of a latino man, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", { input: { model: "dev", prompt: "portrait of a latino man, in the style of TMHNDRD", lora_scale: 1, num_outputs: 1, aspect_ratio: "4:5", output_format: "webp", guidance_scale: 3.5, output_quality: 90, prompt_strength: 0.8, extra_lora_scale: 1, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun lucataco/flux-time100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "lucataco/flux-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", input={ "model": "dev", "prompt": "portrait of a latino man, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run lucataco/flux-time100 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-time100:99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501", "input": { "model": "dev", "prompt": "portrait of a latino man, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-09-09T04:21:50.014632Z", "created_at": "2024-09-09T04:21:34.467000Z", "data_removed": false, "error": null, "id": "h465smfygdrm40chtm1sa4c424", "input": { "model": "dev", "prompt": "portrait of a latino man, in the style of TMHNDRD", "lora_scale": 1, "num_outputs": 1, "aspect_ratio": "4:5", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 90, "prompt_strength": 0.8, "extra_lora_scale": 1, "num_inference_steps": 28 }, "logs": "Using seed: 57618\nPrompt: portrait of a latino man, in the style of TMHNDRD\n[!] txt2img mode\nUsing dev model\nLoaded LoRAs in 7.90s\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:06, 3.96it/s]\n 7%|▋ | 2/28 [00:00<00:05, 4.46it/s]\n 11%|█ | 3/28 [00:00<00:05, 4.21it/s]\n 14%|█▍ | 4/28 [00:00<00:05, 4.10it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 4.03it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 4.00it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.98it/s]\n 29%|██▊ | 8/28 [00:01<00:05, 3.97it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.96it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.96it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.95it/s]\n 43%|████▎ | 12/28 [00:02<00:04, 3.95it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.95it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.95it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.95it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.95it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.95it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.94it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.95it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.94it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.94it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.94it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.94it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.94it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.94it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.94it/s]\n 96%|█████████▋| 27/28 [00:06<00:00, 3.94it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.94it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.97it/s]", "metrics": { "predict_time": 15.506577945, "total_time": 15.547632 }, "output": [ "https://replicate.delivery/yhqm/vL4qJV2foMzeGkT5EYCIj8pixfIerSLs1eN8hRHuZ2mq7UYbC/out-0.webp" ], "started_at": "2024-09-09T04:21:34.508054Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/h465smfygdrm40chtm1sa4c424", "cancel": "https://api.replicate.com/v1/predictions/h465smfygdrm40chtm1sa4c424/cancel" }, "version": "99ffe5dff76558f8b65d012bd35df0d2dddeaf201a23192941945de3b9c55501" }Generated inUsing seed: 57618 Prompt: portrait of a latino man, in the style of TMHNDRD [!] txt2img mode Using dev model Loaded LoRAs in 7.90s 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:06, 3.96it/s] 7%|▋ | 2/28 [00:00<00:05, 4.46it/s] 11%|█ | 3/28 [00:00<00:05, 4.21it/s] 14%|█▍ | 4/28 [00:00<00:05, 4.10it/s] 18%|█▊ | 5/28 [00:01<00:05, 4.03it/s] 21%|██▏ | 6/28 [00:01<00:05, 4.00it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.98it/s] 29%|██▊ | 8/28 [00:01<00:05, 3.97it/s] 32%|███▏ | 9/28 [00:02<00:04, 3.96it/s] 36%|███▌ | 10/28 [00:02<00:04, 3.96it/s] 39%|███▉ | 11/28 [00:02<00:04, 3.95it/s] 43%|████▎ | 12/28 [00:02<00:04, 3.95it/s] 46%|████▋ | 13/28 [00:03<00:03, 3.95it/s] 50%|█████ | 14/28 [00:03<00:03, 3.95it/s] 54%|█████▎ | 15/28 [00:03<00:03, 3.95it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.95it/s] 61%|██████ | 17/28 [00:04<00:02, 3.95it/s] 64%|██████▍ | 18/28 [00:04<00:02, 3.94it/s] 68%|██████▊ | 19/28 [00:04<00:02, 3.95it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.94it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.94it/s] 79%|███████▊ | 22/28 [00:05<00:01, 3.94it/s] 82%|████████▏ | 23/28 [00:05<00:01, 3.94it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.94it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.94it/s] 93%|█████████▎| 26/28 [00:06<00:00, 3.94it/s] 96%|█████████▋| 27/28 [00:06<00:00, 3.94it/s] 100%|██████████| 28/28 [00:07<00:00, 3.94it/s] 100%|██████████| 28/28 [00:07<00:00, 3.97it/s]
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