shapestudio
/
nihon-flux
Fine tuned Lora Japanese style reference. Defaults to traditional red, grey and blue.
- Public
- 357 runs
-
H100
Prediction
shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8bIDt0zba6hep5rm40chdvmtq4ywncStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- koi fish in the style of TOK
- lora_scale
- 0.81
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "koi fish in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", { input: { model: "dev", prompt: "koi fish in the style of TOK", lora_scale: 0.81, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", input={ "model": "dev", "prompt": "koi fish in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run shapestudio/nihon-flux 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": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", "input": { "model": "dev", "prompt": "koi fish in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-20T08:32:45.963023Z", "created_at": "2024-08-20T08:31:01.297000Z", "data_removed": false, "error": null, "id": "t0zba6hep5rm40chdvmtq4ywnc", "input": { "model": "dev", "prompt": "koi fish in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 57869\nPrompt: koi fish in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9416633589760\nDownloading weights\n2024-08-20T08:32:27Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\n2024-08-20T08:32:28Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size=\"172 MB\" total_elapsed=1.246s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\nb''\nDownloaded weights in 1.2718119621276855 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.52it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.92it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.75it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.67it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.61it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.58it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.56it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.53it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.53it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.54it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.54it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.54it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.56it/s]", "metrics": { "predict_time": 18.295082035, "total_time": 104.666023 }, "output": [ "https://replicate.delivery/yhqm/f0wl8oa9J118GCinp0HT7TFey5OFgqtr8pLtVFsHs4ttagUTA/out-0.webp" ], "started_at": "2024-08-20T08:32:27.667941Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/t0zba6hep5rm40chdvmtq4ywnc", "cancel": "https://api.replicate.com/v1/predictions/t0zba6hep5rm40chdvmtq4ywnc/cancel" }, "version": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b" }Generated inUsing seed: 57869 Prompt: koi fish in the style of TOK txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9416633589760 Downloading weights 2024-08-20T08:32:27Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar 2024-08-20T08:32:28Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size="172 MB" total_elapsed=1.246s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar b'' Downloaded weights in 1.2718119621276855 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.52it/s] 7%|▋ | 2/28 [00:00<00:06, 3.92it/s] 11%|█ | 3/28 [00:00<00:06, 3.75it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.67it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.61it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.58it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.56it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.53it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.54it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.54it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.53it/s] 50%|█████ | 14/28 [00:03<00:03, 3.53it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.54it/s] 61%|██████ | 17/28 [00:04<00:03, 3.53it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.53it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.54it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.54it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.54it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.53it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s] 100%|██████████| 28/28 [00:07<00:00, 3.54it/s] 100%|██████████| 28/28 [00:07<00:00, 3.56it/s]Prediction
shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8bID78495th4ehrm20chdvnsrx9tfwStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- samurai and the mountain in the style of TOK
- lora_scale
- 0.81
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "samurai and the mountain in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", { input: { model: "dev", prompt: "samurai and the mountain in the style of TOK", lora_scale: 0.81, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", input={ "model": "dev", "prompt": "samurai and the mountain in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run shapestudio/nihon-flux 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": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", "input": { "model": "dev", "prompt": "samurai and the mountain in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-20T08:33:29.294134Z", "created_at": "2024-08-20T08:33:09.748000Z", "data_removed": false, "error": null, "id": "78495th4ehrm20chdvnsrx9tfw", "input": { "model": "dev", "prompt": "samurai and the mountain in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 4344\nPrompt: samurai and the mountain in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9349287141376\nDownloading weights\n2024-08-20T08:33:09Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\n2024-08-20T08:33:12Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size=\"172 MB\" total_elapsed=2.802s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\nb''\nDownloaded weights in 2.8304781913757324 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:08, 3.34it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.85it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.70it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.61it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.57it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.56it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.56it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.56it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.56it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.55it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.56it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.56it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.56it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.56it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.56it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.55it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.55it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.56it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.56it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.55it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.55it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.56it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.57it/s]", "metrics": { "predict_time": 19.50822317, "total_time": 19.546134 }, "output": [ "https://replicate.delivery/yhqm/rpUm785tt5ZvJpugSqb2FeYQlFeq6afzfh0Sx8DvabbntBSNB/out-0.webp" ], "started_at": "2024-08-20T08:33:09.785911Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/78495th4ehrm20chdvnsrx9tfw", "cancel": "https://api.replicate.com/v1/predictions/78495th4ehrm20chdvnsrx9tfw/cancel" }, "version": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b" }Generated inUsing seed: 4344 Prompt: samurai and the mountain in the style of TOK txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9349287141376 Downloading weights 2024-08-20T08:33:09Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar 2024-08-20T08:33:12Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size="172 MB" total_elapsed=2.802s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar b'' Downloaded weights in 2.8304781913757324 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:08, 3.34it/s] 7%|▋ | 2/28 [00:00<00:06, 3.85it/s] 11%|█ | 3/28 [00:00<00:06, 3.70it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.65it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.61it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.57it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.56it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.56it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.56it/s] 50%|█████ | 14/28 [00:03<00:03, 3.56it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.55it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.56it/s] 61%|██████ | 17/28 [00:04<00:03, 3.56it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.56it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.56it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.56it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.55it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.55it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.56it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.56it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.55it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.55it/s] 100%|██████████| 28/28 [00:07<00:00, 3.56it/s] 100%|██████████| 28/28 [00:07<00:00, 3.57it/s]Prediction
shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8bID7hee2pz3wdrm20chdvpbapwbnmStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- cat and the mouse in the style of TOK
- lora_scale
- 0.81
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "cat and the mouse in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", { input: { model: "dev", prompt: "cat and the mouse in the style of TOK", lora_scale: 0.81, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", input={ "model": "dev", "prompt": "cat and the mouse in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run shapestudio/nihon-flux 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": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", "input": { "model": "dev", "prompt": "cat and the mouse in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-20T08:36:17.590836Z", "created_at": "2024-08-20T08:35:04.291000Z", "data_removed": false, "error": null, "id": "7hee2pz3wdrm20chdvpbapwbnm", "input": { "model": "dev", "prompt": "cat and the mouse in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 48458\nPrompt: cat and the mouse in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9839685947392\nDownloading weights\n2024-08-20T08:35:56Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\n2024-08-20T08:36:00Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size=\"172 MB\" total_elapsed=3.618s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\nb''\nDownloaded weights in 3.6458890438079834 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.54it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.96it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.76it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.67it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.58it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.56it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.56it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.55it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.55it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.55it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.55it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.55it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.55it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.55it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.55it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.55it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.55it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.55it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.54it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.55it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.55it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.57it/s]", "metrics": { "predict_time": 20.743117471, "total_time": 73.299836 }, "output": [ "https://replicate.delivery/yhqm/bNivbEjJEQZJO1TqtWxAUrFIdmqfaKxqzY4EkLURFSsAPQqJA/out-0.webp" ], "started_at": "2024-08-20T08:35:56.847718Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7hee2pz3wdrm20chdvpbapwbnm", "cancel": "https://api.replicate.com/v1/predictions/7hee2pz3wdrm20chdvpbapwbnm/cancel" }, "version": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b" }Generated inUsing seed: 48458 Prompt: cat and the mouse in the style of TOK txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9839685947392 Downloading weights 2024-08-20T08:35:56Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar 2024-08-20T08:36:00Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size="172 MB" total_elapsed=3.618s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar b'' Downloaded weights in 3.6458890438079834 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.54it/s] 7%|▋ | 2/28 [00:00<00:06, 3.96it/s] 11%|█ | 3/28 [00:00<00:06, 3.76it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.67it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.62it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.59it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.58it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.57it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.56it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.56it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.56it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.55it/s] 50%|█████ | 14/28 [00:03<00:03, 3.55it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.55it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.55it/s] 61%|██████ | 17/28 [00:04<00:03, 3.55it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.55it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.55it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.55it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.55it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.55it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.55it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.54it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.55it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.55it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s] 100%|██████████| 28/28 [00:07<00:00, 3.57it/s]Prediction
shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8bIDex3s6j9ga9rm60chdvqv3cska4StatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- woman in the style of TOK
- lora_scale
- 0.81
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "woman in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", { input: { model: "dev", prompt: "woman in the style of TOK", lora_scale: 0.81, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", input={ "model": "dev", "prompt": "woman in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run shapestudio/nihon-flux 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": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", "input": { "model": "dev", "prompt": "woman in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-20T08:38:49.629313Z", "created_at": "2024-08-20T08:37:34.930000Z", "data_removed": false, "error": null, "id": "ex3s6j9ga9rm60chdvqv3cska4", "input": { "model": "dev", "prompt": "woman in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 48483\nPrompt: woman in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9286638292992\nDownloading weights\n2024-08-20T08:38:31Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\n2024-08-20T08:38:33Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size=\"172 MB\" total_elapsed=1.378s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\nb''\nDownloaded weights in 1.4040923118591309 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.53it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.96it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.73it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.69it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.63it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.62it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.60it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.58it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.58it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.57it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.57it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.57it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.57it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.56it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.57it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.55it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.56it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.57it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.56it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.56it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.56it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.57it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.57it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.56it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.56it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.57it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.56it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.58it/s]", "metrics": { "predict_time": 18.07378688, "total_time": 74.699313 }, "output": [ "https://replicate.delivery/yhqm/QjS67bJbknZPE5m3tO5lrH0Fp6rUYaLzNhyPlSmyUwUGII1E/out-0.webp" ], "started_at": "2024-08-20T08:38:31.555526Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ex3s6j9ga9rm60chdvqv3cska4", "cancel": "https://api.replicate.com/v1/predictions/ex3s6j9ga9rm60chdvqv3cska4/cancel" }, "version": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b" }Generated inUsing seed: 48483 Prompt: woman in the style of TOK txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9286638292992 Downloading weights 2024-08-20T08:38:31Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar 2024-08-20T08:38:33Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size="172 MB" total_elapsed=1.378s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar b'' Downloaded weights in 1.4040923118591309 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.53it/s] 7%|▋ | 2/28 [00:00<00:06, 3.96it/s] 11%|█ | 3/28 [00:00<00:06, 3.73it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.69it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.63it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.62it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.60it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.58it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.58it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.57it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.57it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.57it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.57it/s] 50%|█████ | 14/28 [00:03<00:03, 3.56it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.57it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.55it/s] 61%|██████ | 17/28 [00:04<00:03, 3.56it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.57it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.56it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.56it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.56it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.57it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.57it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.56it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.56it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.57it/s] 100%|██████████| 28/28 [00:07<00:00, 3.56it/s] 100%|██████████| 28/28 [00:07<00:00, 3.58it/s]Prediction
shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8bID452vkx6janrm60chdvwskn2j4rStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- perfume bottle on the mountain with the red sun in the style of TOK
- lora_scale
- 0.81
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "perfume bottle on the mountain with the red sun in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", { input: { model: "dev", prompt: "perfume bottle on the mountain with the red sun in the style of TOK", lora_scale: 0.81, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", input={ "model": "dev", "prompt": "perfume bottle on the mountain with the red sun in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run shapestudio/nihon-flux 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": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", "input": { "model": "dev", "prompt": "perfume bottle on the mountain with the red sun in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-20T08:50:02.688486Z", "created_at": "2024-08-20T08:49:11.765000Z", "data_removed": false, "error": null, "id": "452vkx6janrm60chdvwskn2j4r", "input": { "model": "dev", "prompt": "perfume bottle on the mountain with the red sun in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 39717\nPrompt: perfume bottle on the mountain with the red sun in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9486054969344\nDownloading weights\n2024-08-20T08:49:45Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\n2024-08-20T08:49:46Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size=\"172 MB\" total_elapsed=1.430s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\nb''\nDownloaded weights in 1.457927942276001 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.53it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.95it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.75it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.68it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.63it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.60it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.59it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.58it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.57it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.56it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.55it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.53it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.55it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.55it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.55it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.55it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.54it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.55it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.55it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.55it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.55it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.57it/s]", "metrics": { "predict_time": 17.297652505, "total_time": 50.923486 }, "output": [ "https://replicate.delivery/yhqm/2ADOvx32UV41PRrjIOyz9hCia0JvHPGlAfE3BKsPwRBdVQqJA/out-0.webp" ], "started_at": "2024-08-20T08:49:45.390834Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/452vkx6janrm60chdvwskn2j4r", "cancel": "https://api.replicate.com/v1/predictions/452vkx6janrm60chdvwskn2j4r/cancel" }, "version": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b" }Generated inUsing seed: 39717 Prompt: perfume bottle on the mountain with the red sun in the style of TOK txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9486054969344 Downloading weights 2024-08-20T08:49:45Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar 2024-08-20T08:49:46Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size="172 MB" total_elapsed=1.430s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar b'' Downloaded weights in 1.457927942276001 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.53it/s] 7%|▋ | 2/28 [00:00<00:06, 3.95it/s] 11%|█ | 3/28 [00:00<00:06, 3.75it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.68it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.63it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.60it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.59it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.58it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.57it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.56it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.56it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.55it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s] 50%|█████ | 14/28 [00:03<00:03, 3.53it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.55it/s] 61%|██████ | 17/28 [00:04<00:03, 3.55it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.54it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.55it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.55it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.55it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.54it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.55it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.55it/s] 89%|████████▉ | 25/28 [00:06<00:00, 3.55it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.55it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s] 100%|██████████| 28/28 [00:07<00:00, 3.57it/s]Prediction
shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8bIDw2n5kskjd9rm00chdvy95kyvywStatusSucceededSourceWebHardwareH100Total durationCreatedInput
- model
- dev
- prompt
- octopus in the style of TOK
- lora_scale
- 0.81
- num_outputs
- 1
- aspect_ratio
- 1:1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "model": "dev", "prompt": "octopus in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", { input: { model: "dev", prompt: "octopus in the style of TOK", lora_scale: 0.81, num_outputs: 1, aspect_ratio: "1:1", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun shapestudio/nihon-flux using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "shapestudio/nihon-flux:f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", input={ "model": "dev", "prompt": "octopus in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run shapestudio/nihon-flux 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": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b", "input": { "model": "dev", "prompt": "octopus in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "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": "2024-08-20T08:52:52.596460Z", "created_at": "2024-08-20T08:52:03.818000Z", "data_removed": false, "error": null, "id": "w2n5kskjd9rm00chdvy95kyvyw", "input": { "model": "dev", "prompt": "octopus in the style of TOK", "lora_scale": 0.81, "num_outputs": 1, "aspect_ratio": "1:1", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 41574\nPrompt: octopus in the style of TOK\ntxt2img mode\nUsing dev model\nLoading LoRA weights\nEnsuring enough disk space...\nFree disk space: 9593660723200\nDownloading weights\n2024-08-20T08:52:34Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\n2024-08-20T08:52:36Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size=\"172 MB\" total_elapsed=1.405s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar\nb''\nDownloaded weights in 1.4335379600524902 seconds\nLoRA weights loaded successfully\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.51it/s]\n 7%|▋ | 2/28 [00:00<00:06, 3.93it/s]\n 11%|█ | 3/28 [00:00<00:06, 3.75it/s]\n 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s]\n 18%|█▊ | 5/28 [00:01<00:06, 3.59it/s]\n 21%|██▏ | 6/28 [00:01<00:06, 3.58it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.56it/s]\n 32%|███▏ | 9/28 [00:02<00:05, 3.55it/s]\n 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s]\n 39%|███▉ | 11/28 [00:03<00:04, 3.53it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.53it/s]\n 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.54it/s]\n 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.53it/s]\n 61%|██████ | 17/28 [00:04<00:03, 3.52it/s]\n 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s]\n 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s]\n 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s]\n 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s]\n 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s]\n 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.52it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.55it/s]", "metrics": { "predict_time": 17.737467276, "total_time": 48.77846 }, "output": [ "https://replicate.delivery/yhqm/TVEWmW2RulLhGxt48BmZxXXYjz32uIYDoj4PrpXKegcyWQqJA/out-0.webp" ], "started_at": "2024-08-20T08:52:34.858993Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/w2n5kskjd9rm00chdvy95kyvyw", "cancel": "https://api.replicate.com/v1/predictions/w2n5kskjd9rm00chdvy95kyvyw/cancel" }, "version": "f6db42ebb5ab496aeec5bf7a7ef2f6ea8e25785c80a952494fc915ccbe9e3d8b" }Generated inUsing seed: 41574 Prompt: octopus in the style of TOK txt2img mode Using dev model Loading LoRA weights Ensuring enough disk space... Free disk space: 9593660723200 Downloading weights 2024-08-20T08:52:34Z | INFO | [ Initiating ] chunk_size=150M dest=/src/weights-cache/cf881f8047c8e63e url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar 2024-08-20T08:52:36Z | INFO | [ Complete ] dest=/src/weights-cache/cf881f8047c8e63e size="172 MB" total_elapsed=1.405s url=https://replicate.delivery/yhqm/4BUw5c1NY8LAGdadk41ykjnuCVsutRzu7Nr9fH2qqffXvApmA/trained_model.tar b'' Downloaded weights in 1.4335379600524902 seconds LoRA weights loaded successfully 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:07, 3.51it/s] 7%|▋ | 2/28 [00:00<00:06, 3.93it/s] 11%|█ | 3/28 [00:00<00:06, 3.75it/s] 14%|█▍ | 4/28 [00:01<00:06, 3.64it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.59it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.58it/s] 25%|██▌ | 7/28 [00:01<00:05, 3.57it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.56it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.55it/s] 36%|███▌ | 10/28 [00:02<00:05, 3.54it/s] 39%|███▉ | 11/28 [00:03<00:04, 3.53it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.53it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.54it/s] 50%|█████ | 14/28 [00:03<00:03, 3.54it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.54it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.53it/s] 61%|██████ | 17/28 [00:04<00:03, 3.52it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.53it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.54it/s] 71%|███████▏ | 20/28 [00:05<00:02, 3.54it/s] 75%|███████▌ | 21/28 [00:05<00:01, 3.53it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.53it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.53it/s] 86%|████████▌ | 24/28 [00:06<00:01, 3.53it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.53it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.54it/s] 96%|█████████▋| 27/28 [00:07<00:00, 3.53it/s] 100%|██████████| 28/28 [00:07<00:00, 3.52it/s] 100%|██████████| 28/28 [00:07<00:00, 3.55it/s]
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