ashesashes
/
ugly-sweater
Ugly Sweaters: The only garment that screams "Fashion? Never heard of it."
- Public
- 109 runs
-
L40S
- SDXL fine-tune
Prediction
ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82fIDszpy6m3b4amvacnidz6p4xgo7iStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1024
- prompt
- batman wearing a TOK sweater, superhero
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- deformed, blurry, ugly,
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 1024, "prompt": "batman wearing a TOK sweater, superhero", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 }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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", { input: { width: 768, height: 1024, prompt: "batman wearing a TOK sweater, superhero", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "deformed, blurry, ugly, ", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", input={ "width": 768, "height": 1024, "prompt": "batman wearing a TOK sweater, superhero", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run ashesashes/ugly-sweater 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": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", "input": { "width": 768, "height": 1024, "prompt": "batman wearing a TOK sweater, superhero", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-12-20T21:26:00.529395Z", "created_at": "2023-12-20T21:25:41.787630Z", "data_removed": false, "error": null, "id": "szpy6m3b4amvacnidz6p4xgo7i", "input": { "width": 768, "height": 1024, "prompt": "batman wearing a TOK sweater, superhero", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 64441\nEnsuring enough disk space...\nFree disk space: 1987279429632\nDownloading weights: https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\n2023-12-20T21:25:46Z | INFO | [ Initiating ] dest=/src/weights-cache/b245a83e2dc9dde2 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\n2023-12-20T21:25:47Z | INFO | [ Complete ] dest=/src/weights-cache/b245a83e2dc9dde2 size=\"186 MB\" total_elapsed=0.951s url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\nb''\nDownloaded weights in 1.1149499416351318 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: batman wearing a <s0><s1> sweater, superhero\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:10, 4.53it/s]\n 4%|▍ | 2/50 [00:00<00:10, 4.76it/s]\n 6%|▌ | 3/50 [00:00<00:09, 4.83it/s]\n 8%|▊ | 4/50 [00:00<00:09, 4.87it/s]\n 10%|█ | 5/50 [00:01<00:09, 4.89it/s]\n 12%|█▏ | 6/50 [00:01<00:08, 4.90it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.91it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.91it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.91it/s]\n 20%|██ | 10/50 [00:02<00:08, 4.90it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.91it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.91it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.91it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.90it/s]\n 30%|███ | 15/50 [00:03<00:07, 4.90it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.90it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.90it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.90it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.89it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.90it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.90it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.90it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.90it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.89it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.90it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.89it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.90it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.90it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.89it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.89it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.89it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.89it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.89it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.88it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.89it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.89it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.89it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.89it/s]\n 78%|███████▊ | 39/50 [00:07<00:02, 4.89it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.89it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.89it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.89it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.89it/s]\n 88%|████████▊ | 44/50 [00:08<00:01, 4.89it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.89it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.88it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.89it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.89it/s]\n 98%|█████████▊| 49/50 [00:10<00:00, 4.88it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.89it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.89it/s]", "metrics": { "predict_time": 14.028936, "total_time": 18.741765 }, "output": [ "https://replicate.delivery/pbxt/ivMbwvAVBLZnA5fA17nXtmtKy1E3UhdEaMain31RXNvzbICJA/out-0.png" ], "started_at": "2023-12-20T21:25:46.500459Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/szpy6m3b4amvacnidz6p4xgo7i", "cancel": "https://api.replicate.com/v1/predictions/szpy6m3b4amvacnidz6p4xgo7i/cancel" }, "version": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f" }Generated inUsing seed: 64441 Ensuring enough disk space... Free disk space: 1987279429632 Downloading weights: https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar 2023-12-20T21:25:46Z | INFO | [ Initiating ] dest=/src/weights-cache/b245a83e2dc9dde2 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar 2023-12-20T21:25:47Z | INFO | [ Complete ] dest=/src/weights-cache/b245a83e2dc9dde2 size="186 MB" total_elapsed=0.951s url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar b'' Downloaded weights in 1.1149499416351318 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: batman wearing a <s0><s1> sweater, superhero txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:10, 4.53it/s] 4%|▍ | 2/50 [00:00<00:10, 4.76it/s] 6%|▌ | 3/50 [00:00<00:09, 4.83it/s] 8%|▊ | 4/50 [00:00<00:09, 4.87it/s] 10%|█ | 5/50 [00:01<00:09, 4.89it/s] 12%|█▏ | 6/50 [00:01<00:08, 4.90it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.91it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.91it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.91it/s] 20%|██ | 10/50 [00:02<00:08, 4.90it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.91it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.91it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.91it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.90it/s] 30%|███ | 15/50 [00:03<00:07, 4.90it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.90it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.90it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.90it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.89it/s] 40%|████ | 20/50 [00:04<00:06, 4.90it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.90it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.90it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.90it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.89it/s] 50%|█████ | 25/50 [00:05<00:05, 4.90it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.89it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.90it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.90it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.89it/s] 60%|██████ | 30/50 [00:06<00:04, 4.89it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.89it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.89it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.89it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.88it/s] 70%|███████ | 35/50 [00:07<00:03, 4.89it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.89it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.89it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.89it/s] 78%|███████▊ | 39/50 [00:07<00:02, 4.89it/s] 80%|████████ | 40/50 [00:08<00:02, 4.89it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.89it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.89it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.89it/s] 88%|████████▊ | 44/50 [00:08<00:01, 4.89it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.89it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.88it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.89it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.89it/s] 98%|█████████▊| 49/50 [00:10<00:00, 4.88it/s] 100%|██████████| 50/50 [00:10<00:00, 4.89it/s] 100%|██████████| 50/50 [00:10<00:00, 4.89it/s]Prediction
ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82fIDloggxgdb76ohiaiqdzkbzawdwaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1024
- prompt
- emma watson as Hermione Granger wearing a TOK sweater, gryffindor
- refine
- no_refiner
- scheduler
- KarrasDPM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- negative_prompt
- deformed, blurry, ugly,
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 1024, "prompt": "emma watson as Hermione Granger wearing a TOK sweater, gryffindor", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 }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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", { input: { width: 768, height: 1024, prompt: "emma watson as Hermione Granger wearing a TOK sweater, gryffindor", refine: "no_refiner", scheduler: "KarrasDPM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, negative_prompt: "deformed, blurry, ugly, ", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", input={ "width": 768, "height": 1024, "prompt": "emma watson as Hermione Granger wearing a TOK sweater, gryffindor", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run ashesashes/ugly-sweater 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": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", "input": { "width": 768, "height": 1024, "prompt": "emma watson as Hermione Granger wearing a TOK sweater, gryffindor", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-12-20T21:30:27.065156Z", "created_at": "2023-12-20T21:30:06.458685Z", "data_removed": false, "error": null, "id": "loggxgdb76ohiaiqdzkbzawdwa", "input": { "width": 768, "height": 1024, "prompt": "emma watson as Hermione Granger wearing a TOK sweater, gryffindor", "refine": "no_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "negative_prompt": "deformed, blurry, ugly, ", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 36260\nEnsuring enough disk space...\nFree disk space: 2344002809856\nDownloading weights: https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\n2023-12-20T21:30:13Z | INFO | [ Initiating ] dest=/src/weights-cache/b245a83e2dc9dde2 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\n2023-12-20T21:30:14Z | INFO | [ Complete ] dest=/src/weights-cache/b245a83e2dc9dde2 size=\"186 MB\" total_elapsed=0.697s url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\nb''\nDownloaded weights in 0.8649864196777344 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: emma watson as Hermione Granger wearing a <s0><s1> sweater, gryffindor\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:10, 4.55it/s]\n 4%|▍ | 2/50 [00:00<00:10, 4.74it/s]\n 6%|▌ | 3/50 [00:00<00:09, 4.80it/s]\n 8%|▊ | 4/50 [00:00<00:09, 4.83it/s]\n 10%|█ | 5/50 [00:01<00:09, 4.84it/s]\n 12%|█▏ | 6/50 [00:01<00:09, 4.84it/s]\n 14%|█▍ | 7/50 [00:01<00:08, 4.85it/s]\n 16%|█▌ | 8/50 [00:01<00:08, 4.86it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.87it/s]\n 20%|██ | 10/50 [00:02<00:08, 4.87it/s]\n 22%|██▏ | 11/50 [00:02<00:07, 4.88it/s]\n 24%|██▍ | 12/50 [00:02<00:07, 4.89it/s]\n 26%|██▌ | 13/50 [00:02<00:07, 4.89it/s]\n 28%|██▊ | 14/50 [00:02<00:07, 4.88it/s]\n 30%|███ | 15/50 [00:03<00:07, 4.88it/s]\n 32%|███▏ | 16/50 [00:03<00:06, 4.89it/s]\n 34%|███▍ | 17/50 [00:03<00:06, 4.89it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.89it/s]\n 38%|███▊ | 19/50 [00:03<00:06, 4.89it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.89it/s]\n 42%|████▏ | 21/50 [00:04<00:05, 4.89it/s]\n 44%|████▍ | 22/50 [00:04<00:05, 4.89it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.88it/s]\n 48%|████▊ | 24/50 [00:04<00:05, 4.89it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.88it/s]\n 52%|█████▏ | 26/50 [00:05<00:04, 4.88it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.89it/s]\n 56%|█████▌ | 28/50 [00:05<00:04, 4.89it/s]\n 58%|█████▊ | 29/50 [00:05<00:04, 4.88it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.88it/s]\n 62%|██████▏ | 31/50 [00:06<00:03, 4.88it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.88it/s]\n 66%|██████▌ | 33/50 [00:06<00:03, 4.88it/s]\n 68%|██████▊ | 34/50 [00:06<00:03, 4.88it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.88it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.88it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.88it/s]\n 76%|███████▌ | 38/50 [00:07<00:02, 4.88it/s]\n 78%|███████▊ | 39/50 [00:08<00:02, 4.88it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.88it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.88it/s]\n 84%|████████▍ | 42/50 [00:08<00:01, 4.88it/s]\n 86%|████████▌ | 43/50 [00:08<00:01, 4.87it/s]\n 88%|████████▊ | 44/50 [00:09<00:01, 4.87it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.88it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.88it/s]\n 94%|█████████▍| 47/50 [00:09<00:00, 4.88it/s]\n 96%|█████████▌| 48/50 [00:09<00:00, 4.87it/s]\n98%|█████████▊| 49/50 [00:10<00:00, 4.88it/s]\n98%|█████████▊| 49/50 [00:10<00:00, 4.87it/s]", "metrics": { "predict_time": 13.708093, "total_time": 20.606471 }, "output": [ "https://replicate.delivery/pbxt/XT16w2XKbv6RKFaGokbL5Odujy6KwJxhh3sFDZdYiJc8OEhE/out-0.png" ], "started_at": "2023-12-20T21:30:13.357063Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/loggxgdb76ohiaiqdzkbzawdwa", "cancel": "https://api.replicate.com/v1/predictions/loggxgdb76ohiaiqdzkbzawdwa/cancel" }, "version": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f" }Generated inUsing seed: 36260 Ensuring enough disk space... Free disk space: 2344002809856 Downloading weights: https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar 2023-12-20T21:30:13Z | INFO | [ Initiating ] dest=/src/weights-cache/b245a83e2dc9dde2 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar 2023-12-20T21:30:14Z | INFO | [ Complete ] dest=/src/weights-cache/b245a83e2dc9dde2 size="186 MB" total_elapsed=0.697s url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar b'' Downloaded weights in 0.8649864196777344 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: emma watson as Hermione Granger wearing a <s0><s1> sweater, gryffindor txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:10, 4.55it/s] 4%|▍ | 2/50 [00:00<00:10, 4.74it/s] 6%|▌ | 3/50 [00:00<00:09, 4.80it/s] 8%|▊ | 4/50 [00:00<00:09, 4.83it/s] 10%|█ | 5/50 [00:01<00:09, 4.84it/s] 12%|█▏ | 6/50 [00:01<00:09, 4.84it/s] 14%|█▍ | 7/50 [00:01<00:08, 4.85it/s] 16%|█▌ | 8/50 [00:01<00:08, 4.86it/s] 18%|█▊ | 9/50 [00:01<00:08, 4.87it/s] 20%|██ | 10/50 [00:02<00:08, 4.87it/s] 22%|██▏ | 11/50 [00:02<00:07, 4.88it/s] 24%|██▍ | 12/50 [00:02<00:07, 4.89it/s] 26%|██▌ | 13/50 [00:02<00:07, 4.89it/s] 28%|██▊ | 14/50 [00:02<00:07, 4.88it/s] 30%|███ | 15/50 [00:03<00:07, 4.88it/s] 32%|███▏ | 16/50 [00:03<00:06, 4.89it/s] 34%|███▍ | 17/50 [00:03<00:06, 4.89it/s] 36%|███▌ | 18/50 [00:03<00:06, 4.89it/s] 38%|███▊ | 19/50 [00:03<00:06, 4.89it/s] 40%|████ | 20/50 [00:04<00:06, 4.89it/s] 42%|████▏ | 21/50 [00:04<00:05, 4.89it/s] 44%|████▍ | 22/50 [00:04<00:05, 4.89it/s] 46%|████▌ | 23/50 [00:04<00:05, 4.88it/s] 48%|████▊ | 24/50 [00:04<00:05, 4.89it/s] 50%|█████ | 25/50 [00:05<00:05, 4.88it/s] 52%|█████▏ | 26/50 [00:05<00:04, 4.88it/s] 54%|█████▍ | 27/50 [00:05<00:04, 4.89it/s] 56%|█████▌ | 28/50 [00:05<00:04, 4.89it/s] 58%|█████▊ | 29/50 [00:05<00:04, 4.88it/s] 60%|██████ | 30/50 [00:06<00:04, 4.88it/s] 62%|██████▏ | 31/50 [00:06<00:03, 4.88it/s] 64%|██████▍ | 32/50 [00:06<00:03, 4.88it/s] 66%|██████▌ | 33/50 [00:06<00:03, 4.88it/s] 68%|██████▊ | 34/50 [00:06<00:03, 4.88it/s] 70%|███████ | 35/50 [00:07<00:03, 4.88it/s] 72%|███████▏ | 36/50 [00:07<00:02, 4.88it/s] 74%|███████▍ | 37/50 [00:07<00:02, 4.88it/s] 76%|███████▌ | 38/50 [00:07<00:02, 4.88it/s] 78%|███████▊ | 39/50 [00:08<00:02, 4.88it/s] 80%|████████ | 40/50 [00:08<00:02, 4.88it/s] 82%|████████▏ | 41/50 [00:08<00:01, 4.88it/s] 84%|████████▍ | 42/50 [00:08<00:01, 4.88it/s] 86%|████████▌ | 43/50 [00:08<00:01, 4.87it/s] 88%|████████▊ | 44/50 [00:09<00:01, 4.87it/s] 90%|█████████ | 45/50 [00:09<00:01, 4.88it/s] 92%|█████████▏| 46/50 [00:09<00:00, 4.88it/s] 94%|█████████▍| 47/50 [00:09<00:00, 4.88it/s] 96%|█████████▌| 48/50 [00:09<00:00, 4.87it/s] 98%|█████████▊| 49/50 [00:10<00:00, 4.88it/s] 98%|█████████▊| 49/50 [00:10<00:00, 4.87it/s]Prediction
ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82fIDgeyrsn3bn2l4su4k4zigxfxv64StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1024
- prompt
- Daniel Radcliffe as Harry Potter wearing a TOK sweater, gryffindor, hogwarts
- refine
- expert_ensemble_refiner
- scheduler
- KarrasDPM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- deformed, blurry, ugly, extra limbs
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 1024, "prompt": "Daniel Radcliffe as Harry Potter wearing a TOK sweater, gryffindor, hogwarts ", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 }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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", { input: { width: 768, height: 1024, prompt: "Daniel Radcliffe as Harry Potter wearing a TOK sweater, gryffindor, hogwarts ", refine: "expert_ensemble_refiner", scheduler: "KarrasDPM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.95, negative_prompt: "deformed, blurry, ugly, extra limbs ", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", input={ "width": 768, "height": 1024, "prompt": "Daniel Radcliffe as Harry Potter wearing a TOK sweater, gryffindor, hogwarts ", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run ashesashes/ugly-sweater 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": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", "input": { "width": 768, "height": 1024, "prompt": "Daniel Radcliffe as Harry Potter wearing a TOK sweater, gryffindor, hogwarts ", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-12-20T21:38:01.646645Z", "created_at": "2023-12-20T21:37:43.991421Z", "data_removed": false, "error": null, "id": "geyrsn3bn2l4su4k4zigxfxv64", "input": { "width": 768, "height": 1024, "prompt": "Daniel Radcliffe as Harry Potter wearing a TOK sweater, gryffindor, hogwarts ", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 63150\nEnsuring enough disk space...\nFree disk space: 2076322828288\nDownloading weights: https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\n2023-12-20T21:37:51Z | INFO | [ Initiating ] dest=/src/weights-cache/b245a83e2dc9dde2 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\n2023-12-20T21:37:51Z | INFO | [ Complete ] dest=/src/weights-cache/b245a83e2dc9dde2 size=\"186 MB\" total_elapsed=0.432s url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar\nb''\nDownloaded weights in 0.573728084564209 seconds\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: Daniel Radcliffe as Harry Potter wearing a <s0><s1> sweater, gryffindor, hogwarts\ntxt2img mode\n 0%| | 0/38 [00:00<?, ?it/s]\n 3%|▎ | 1/38 [00:00<00:08, 4.61it/s]\n 5%|▌ | 2/38 [00:00<00:07, 4.81it/s]\n 8%|▊ | 3/38 [00:00<00:07, 4.88it/s]\n 11%|█ | 4/38 [00:00<00:06, 4.91it/s]\n 13%|█▎ | 5/38 [00:01<00:06, 4.92it/s]\n 16%|█▌ | 6/38 [00:01<00:06, 4.93it/s]\n 18%|█▊ | 7/38 [00:01<00:06, 4.94it/s]\n 21%|██ | 8/38 [00:01<00:06, 4.95it/s]\n 24%|██▎ | 9/38 [00:01<00:05, 4.95it/s]\n 26%|██▋ | 10/38 [00:02<00:05, 4.95it/s]\n 29%|██▉ | 11/38 [00:02<00:05, 4.95it/s]\n 32%|███▏ | 12/38 [00:02<00:05, 4.95it/s]\n 34%|███▍ | 13/38 [00:02<00:05, 4.96it/s]\n 37%|███▋ | 14/38 [00:02<00:04, 4.96it/s]\n 39%|███▉ | 15/38 [00:03<00:04, 4.96it/s]\n 42%|████▏ | 16/38 [00:03<00:04, 4.96it/s]\n 45%|████▍ | 17/38 [00:03<00:04, 4.96it/s]\n 47%|████▋ | 18/38 [00:03<00:04, 4.96it/s]\n 50%|█████ | 19/38 [00:03<00:03, 4.96it/s]\n 53%|█████▎ | 20/38 [00:04<00:03, 4.97it/s]\n 55%|█████▌ | 21/38 [00:04<00:03, 4.97it/s]\n 58%|█████▊ | 22/38 [00:04<00:03, 4.97it/s]\n 61%|██████ | 23/38 [00:04<00:03, 4.97it/s]\n 63%|██████▎ | 24/38 [00:04<00:02, 4.97it/s]\n 66%|██████▌ | 25/38 [00:05<00:02, 4.97it/s]\n 68%|██████▊ | 26/38 [00:05<00:02, 4.97it/s]\n 71%|███████ | 27/38 [00:05<00:02, 4.97it/s]\n 74%|███████▎ | 28/38 [00:05<00:02, 4.97it/s]\n 76%|███████▋ | 29/38 [00:05<00:01, 4.97it/s]\n 79%|███████▉ | 30/38 [00:06<00:01, 4.97it/s]\n 82%|████████▏ | 31/38 [00:06<00:01, 4.97it/s]\n 84%|████████▍ | 32/38 [00:06<00:01, 4.97it/s]\n 87%|████████▋ | 33/38 [00:06<00:01, 4.97it/s]\n 89%|████████▉ | 34/38 [00:06<00:00, 4.97it/s]\n 92%|█████████▏| 35/38 [00:07<00:00, 4.97it/s]\n 95%|█████████▍| 36/38 [00:07<00:00, 4.97it/s]\n 97%|█████████▋| 37/38 [00:07<00:00, 4.97it/s]\n100%|██████████| 38/38 [00:07<00:00, 4.96it/s]\n100%|██████████| 38/38 [00:07<00:00, 4.96it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.77it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 6.02it/s]\n100%|██████████| 3/3 [00:00<00:00, 6.09it/s]\n100%|██████████| 3/3 [00:00<00:00, 6.04it/s]", "metrics": { "predict_time": 10.688023, "total_time": 17.655224 }, "output": [ "https://replicate.delivery/pbxt/vCRkwXw0k26eIqxGKyqNLlvxsNkjkfEAl4d7otoIqg65CRESA/out-0.png" ], "started_at": "2023-12-20T21:37:50.958622Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/geyrsn3bn2l4su4k4zigxfxv64", "cancel": "https://api.replicate.com/v1/predictions/geyrsn3bn2l4su4k4zigxfxv64/cancel" }, "version": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f" }Generated inUsing seed: 63150 Ensuring enough disk space... Free disk space: 2076322828288 Downloading weights: https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar 2023-12-20T21:37:51Z | INFO | [ Initiating ] dest=/src/weights-cache/b245a83e2dc9dde2 minimum_chunk_size=150M url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar 2023-12-20T21:37:51Z | INFO | [ Complete ] dest=/src/weights-cache/b245a83e2dc9dde2 size="186 MB" total_elapsed=0.432s url=https://replicate.delivery/pbxt/hvDO7VC9RR7eHKvoHxzDoNkHf0CvpIw8o7yxY7uzE67ryQESA/trained_model.tar b'' Downloaded weights in 0.573728084564209 seconds Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: Daniel Radcliffe as Harry Potter wearing a <s0><s1> sweater, gryffindor, hogwarts txt2img mode 0%| | 0/38 [00:00<?, ?it/s] 3%|▎ | 1/38 [00:00<00:08, 4.61it/s] 5%|▌ | 2/38 [00:00<00:07, 4.81it/s] 8%|▊ | 3/38 [00:00<00:07, 4.88it/s] 11%|█ | 4/38 [00:00<00:06, 4.91it/s] 13%|█▎ | 5/38 [00:01<00:06, 4.92it/s] 16%|█▌ | 6/38 [00:01<00:06, 4.93it/s] 18%|█▊ | 7/38 [00:01<00:06, 4.94it/s] 21%|██ | 8/38 [00:01<00:06, 4.95it/s] 24%|██▎ | 9/38 [00:01<00:05, 4.95it/s] 26%|██▋ | 10/38 [00:02<00:05, 4.95it/s] 29%|██▉ | 11/38 [00:02<00:05, 4.95it/s] 32%|███▏ | 12/38 [00:02<00:05, 4.95it/s] 34%|███▍ | 13/38 [00:02<00:05, 4.96it/s] 37%|███▋ | 14/38 [00:02<00:04, 4.96it/s] 39%|███▉ | 15/38 [00:03<00:04, 4.96it/s] 42%|████▏ | 16/38 [00:03<00:04, 4.96it/s] 45%|████▍ | 17/38 [00:03<00:04, 4.96it/s] 47%|████▋ | 18/38 [00:03<00:04, 4.96it/s] 50%|█████ | 19/38 [00:03<00:03, 4.96it/s] 53%|█████▎ | 20/38 [00:04<00:03, 4.97it/s] 55%|█████▌ | 21/38 [00:04<00:03, 4.97it/s] 58%|█████▊ | 22/38 [00:04<00:03, 4.97it/s] 61%|██████ | 23/38 [00:04<00:03, 4.97it/s] 63%|██████▎ | 24/38 [00:04<00:02, 4.97it/s] 66%|██████▌ | 25/38 [00:05<00:02, 4.97it/s] 68%|██████▊ | 26/38 [00:05<00:02, 4.97it/s] 71%|███████ | 27/38 [00:05<00:02, 4.97it/s] 74%|███████▎ | 28/38 [00:05<00:02, 4.97it/s] 76%|███████▋ | 29/38 [00:05<00:01, 4.97it/s] 79%|███████▉ | 30/38 [00:06<00:01, 4.97it/s] 82%|████████▏ | 31/38 [00:06<00:01, 4.97it/s] 84%|████████▍ | 32/38 [00:06<00:01, 4.97it/s] 87%|████████▋ | 33/38 [00:06<00:01, 4.97it/s] 89%|████████▉ | 34/38 [00:06<00:00, 4.97it/s] 92%|█████████▏| 35/38 [00:07<00:00, 4.97it/s] 95%|█████████▍| 36/38 [00:07<00:00, 4.97it/s] 97%|█████████▋| 37/38 [00:07<00:00, 4.97it/s] 100%|██████████| 38/38 [00:07<00:00, 4.96it/s] 100%|██████████| 38/38 [00:07<00:00, 4.96it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.77it/s] 67%|██████▋ | 2/3 [00:00<00:00, 6.02it/s] 100%|██████████| 3/3 [00:00<00:00, 6.09it/s] 100%|██████████| 3/3 [00:00<00:00, 6.04it/s]Prediction
ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82fID7cgdcblbubq4rmygdrcgpj3xaiStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 768
- height
- 1024
- prompt
- a corgi wearing a TOK sweater
- refine
- expert_ensemble_refiner
- scheduler
- KarrasDPM
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- deformed, blurry, ugly, extra limbs
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 768, "height": 1024, "prompt": "a corgi wearing a TOK sweater", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 }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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", { input: { width: 768, height: 1024, prompt: "a corgi wearing a TOK sweater", refine: "expert_ensemble_refiner", scheduler: "KarrasDPM", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "deformed, blurry, ugly, extra limbs ", prompt_strength: 0.8, num_inference_steps: 50 } } ); // 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 ashesashes/ugly-sweater using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "ashesashes/ugly-sweater:74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", input={ "width": 768, "height": 1024, "prompt": "a corgi wearing a TOK sweater", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run ashesashes/ugly-sweater 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": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f", "input": { "width": 768, "height": 1024, "prompt": "a corgi wearing a TOK sweater", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-12-20T21:41:03.028286Z", "created_at": "2023-12-20T21:40:50.888916Z", "data_removed": false, "error": null, "id": "7cgdcblbubq4rmygdrcgpj3xai", "input": { "width": 768, "height": 1024, "prompt": "a corgi wearing a TOK sweater", "refine": "expert_ensemble_refiner", "scheduler": "KarrasDPM", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "deformed, blurry, ugly, extra limbs ", "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 62806\nLoading fine-tuned model\nDoes not have Unet. assume we are using LoRA\nLoading Unet LoRA\nPrompt: a corgi wearing a <s0><s1> sweater\ntxt2img mode\n 0%| | 0/38 [00:00<?, ?it/s]\n 3%|▎ | 1/38 [00:00<00:07, 4.95it/s]\n 5%|▌ | 2/38 [00:00<00:07, 4.94it/s]\n 8%|▊ | 3/38 [00:00<00:07, 4.92it/s]\n 11%|█ | 4/38 [00:00<00:06, 4.91it/s]\n 13%|█▎ | 5/38 [00:01<00:06, 4.90it/s]\n 16%|█▌ | 6/38 [00:01<00:06, 4.89it/s]\n 18%|█▊ | 7/38 [00:01<00:06, 4.89it/s]\n 21%|██ | 8/38 [00:01<00:06, 4.89it/s]\n 24%|██▎ | 9/38 [00:01<00:05, 4.89it/s]\n 26%|██▋ | 10/38 [00:02<00:05, 4.88it/s]\n 29%|██▉ | 11/38 [00:02<00:05, 4.87it/s]\n 32%|███▏ | 12/38 [00:02<00:05, 4.87it/s]\n 34%|███▍ | 13/38 [00:02<00:05, 4.88it/s]\n 37%|███▋ | 14/38 [00:02<00:04, 4.88it/s]\n 39%|███▉ | 15/38 [00:03<00:04, 4.88it/s]\n 42%|████▏ | 16/38 [00:03<00:04, 4.87it/s]\n 45%|████▍ | 17/38 [00:03<00:04, 4.88it/s]\n 47%|████▋ | 18/38 [00:03<00:04, 4.88it/s]\n 50%|█████ | 19/38 [00:03<00:03, 4.88it/s]\n 53%|█████▎ | 20/38 [00:04<00:03, 4.88it/s]\n 55%|█████▌ | 21/38 [00:04<00:03, 4.87it/s]\n 58%|█████▊ | 22/38 [00:04<00:03, 4.87it/s]\n 61%|██████ | 23/38 [00:04<00:03, 4.88it/s]\n 63%|██████▎ | 24/38 [00:04<00:02, 4.87it/s]\n 66%|██████▌ | 25/38 [00:05<00:02, 4.88it/s]\n 68%|██████▊ | 26/38 [00:05<00:02, 4.87it/s]\n 71%|███████ | 27/38 [00:05<00:02, 4.87it/s]\n 74%|███████▎ | 28/38 [00:05<00:02, 4.87it/s]\n 76%|███████▋ | 29/38 [00:05<00:01, 4.87it/s]\n 79%|███████▉ | 30/38 [00:06<00:01, 4.87it/s]\n 82%|████████▏ | 31/38 [00:06<00:01, 4.88it/s]\n 84%|████████▍ | 32/38 [00:06<00:01, 4.87it/s]\n 87%|████████▋ | 33/38 [00:06<00:01, 4.87it/s]\n 89%|████████▉ | 34/38 [00:06<00:00, 4.87it/s]\n 92%|█████████▏| 35/38 [00:07<00:00, 4.88it/s]\n 95%|█████████▍| 36/38 [00:07<00:00, 4.88it/s]\n 97%|█████████▋| 37/38 [00:07<00:00, 4.87it/s]\n100%|██████████| 38/38 [00:07<00:00, 4.87it/s]\n100%|██████████| 38/38 [00:07<00:00, 4.88it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 5.57it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 5.85it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.93it/s]\n100%|██████████| 3/3 [00:00<00:00, 5.88it/s]", "metrics": { "predict_time": 10.893684, "total_time": 12.13937 }, "output": [ "https://replicate.delivery/pbxt/k6AXKz5re1w2WCFkySZu9ZNKak1Kkuxrfbs90nR5hKRuFRESA/out-0.png" ], "started_at": "2023-12-20T21:40:52.134602Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7cgdcblbubq4rmygdrcgpj3xai", "cancel": "https://api.replicate.com/v1/predictions/7cgdcblbubq4rmygdrcgpj3xai/cancel" }, "version": "74cdb4a7ceaeda1bc758f379d5915831032c2219080033671eaa5908ab6da82f" }Generated inUsing seed: 62806 Loading fine-tuned model Does not have Unet. assume we are using LoRA Loading Unet LoRA Prompt: a corgi wearing a <s0><s1> sweater txt2img mode 0%| | 0/38 [00:00<?, ?it/s] 3%|▎ | 1/38 [00:00<00:07, 4.95it/s] 5%|▌ | 2/38 [00:00<00:07, 4.94it/s] 8%|▊ | 3/38 [00:00<00:07, 4.92it/s] 11%|█ | 4/38 [00:00<00:06, 4.91it/s] 13%|█▎ | 5/38 [00:01<00:06, 4.90it/s] 16%|█▌ | 6/38 [00:01<00:06, 4.89it/s] 18%|█▊ | 7/38 [00:01<00:06, 4.89it/s] 21%|██ | 8/38 [00:01<00:06, 4.89it/s] 24%|██▎ | 9/38 [00:01<00:05, 4.89it/s] 26%|██▋ | 10/38 [00:02<00:05, 4.88it/s] 29%|██▉ | 11/38 [00:02<00:05, 4.87it/s] 32%|███▏ | 12/38 [00:02<00:05, 4.87it/s] 34%|███▍ | 13/38 [00:02<00:05, 4.88it/s] 37%|███▋ | 14/38 [00:02<00:04, 4.88it/s] 39%|███▉ | 15/38 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100%|██████████| 38/38 [00:07<00:00, 4.87it/s] 100%|██████████| 38/38 [00:07<00:00, 4.88it/s] 0%| | 0/3 [00:00<?, ?it/s] 33%|███▎ | 1/3 [00:00<00:00, 5.57it/s] 67%|██████▋ | 2/3 [00:00<00:00, 5.85it/s] 100%|██████████| 3/3 [00:00<00:00, 5.93it/s] 100%|██████████| 3/3 [00:00<00:00, 5.88it/s]
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