fofr / sdxl-labyrinth
An SDXL fine-tune based on the Labyrinth movie
- Public
- 800 runs
-
L40S
- SDXL fine-tune
Prediction
fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2IDmonnxw3bucsrltsamc5ooitmrmStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- A monster in a bedroom in the style of TOK
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- broken, distorted, disfigured
- prompt_strength
- 0.85
- num_inference_steps
- 40
{ "width": 1152, "height": 768, "prompt": "A monster in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 }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 fofr/sdxl-labyrinth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", { input: { width: 1152, height: 768, prompt: "A monster in a bedroom in the style of TOK", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "broken, distorted, disfigured", prompt_strength: 0.85, num_inference_steps: 40 } } ); // 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 fofr/sdxl-labyrinth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", input={ "width": 1152, "height": 768, "prompt": "A monster in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-labyrinth 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": "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", "input": { "width": 1152, "height": 768, "prompt": "A monster in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-01T22:14:32.498843Z", "created_at": "2023-09-01T22:14:21.504722Z", "data_removed": false, "error": null, "id": "monnxw3bucsrltsamc5ooitmrm", "input": { "width": 1152, "height": 768, "prompt": "A monster in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 }, "logs": "Using seed: 39271\nPrompt: A monster in a bedroom in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/38 [00:00<?, ?it/s]\n 3%|▎ | 1/38 [00:00<00:08, 4.33it/s]\n 5%|▌ | 2/38 [00:00<00:08, 4.33it/s]\n 8%|▊ | 3/38 [00:00<00:08, 4.33it/s]\n 11%|█ | 4/38 [00:00<00:07, 4.33it/s]\n 13%|█▎ | 5/38 [00:01<00:07, 4.33it/s]\n 16%|█▌ | 6/38 [00:01<00:07, 4.32it/s]\n 18%|█▊ | 7/38 [00:01<00:07, 4.32it/s]\n 21%|██ | 8/38 [00:01<00:06, 4.32it/s]\n 24%|██▎ | 9/38 [00:02<00:06, 4.32it/s]\n 26%|██▋ | 10/38 [00:02<00:06, 4.32it/s]\n 29%|██▉ | 11/38 [00:02<00:06, 4.32it/s]\n 32%|███▏ | 12/38 [00:02<00:06, 4.31it/s]\n 34%|███▍ | 13/38 [00:03<00:05, 4.32it/s]\n 37%|███▋ | 14/38 [00:03<00:05, 4.31it/s]\n 39%|███▉ | 15/38 [00:03<00:05, 4.31it/s]\n 42%|████▏ | 16/38 [00:03<00:05, 4.31it/s]\n 45%|████▍ | 17/38 [00:03<00:04, 4.31it/s]\n 47%|████▋ | 18/38 [00:04<00:04, 4.31it/s]\n 50%|█████ | 19/38 [00:04<00:04, 4.31it/s]\n 53%|█████▎ | 20/38 [00:04<00:04, 4.31it/s]\n 55%|█████▌ | 21/38 [00:04<00:03, 4.31it/s]\n 58%|█████▊ | 22/38 [00:05<00:03, 4.31it/s]\n 61%|██████ | 23/38 [00:05<00:03, 4.31it/s]\n 63%|██████▎ | 24/38 [00:05<00:03, 4.31it/s]\n 66%|██████▌ | 25/38 [00:05<00:03, 4.31it/s]\n 68%|██████▊ | 26/38 [00:06<00:02, 4.31it/s]\n 71%|███████ | 27/38 [00:06<00:02, 4.31it/s]\n 74%|███████▎ | 28/38 [00:06<00:02, 4.30it/s]\n 76%|███████▋ | 29/38 [00:06<00:02, 4.31it/s]\n 79%|███████▉ | 30/38 [00:06<00:01, 4.31it/s]\n 82%|████████▏ | 31/38 [00:07<00:01, 4.31it/s]\n 84%|████████▍ | 32/38 [00:07<00:01, 4.30it/s]\n 87%|████████▋ | 33/38 [00:07<00:01, 4.31it/s]\n 89%|████████▉ | 34/38 [00:07<00:00, 4.30it/s]\n 92%|█████████▏| 35/38 [00:08<00:00, 4.31it/s]\n 95%|█████████▍| 36/38 [00:08<00:00, 4.30it/s]\n 97%|█████████▋| 37/38 [00:08<00:00, 4.30it/s]\n100%|██████████| 38/38 [00:08<00:00, 4.30it/s]\n100%|██████████| 38/38 [00:08<00:00, 4.31it/s]\n 0%| | 0/2 [00:00<?, ?it/s]\n 50%|█████ | 1/2 [00:00<00:00, 5.61it/s]\n100%|██████████| 2/2 [00:00<00:00, 5.56it/s]\n100%|██████████| 2/2 [00:00<00:00, 5.57it/s]", "metrics": { "predict_time": 10.994173, "total_time": 10.994121 }, "output": [ "https://replicate.delivery/pbxt/0edAPl7EbJxwKC3boVN1j7laCinSRe1j3nOOx1VcZWiHRBgRA/out-0.png" ], "started_at": "2023-09-01T22:14:21.504670Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/monnxw3bucsrltsamc5ooitmrm", "cancel": "https://api.replicate.com/v1/predictions/monnxw3bucsrltsamc5ooitmrm/cancel" }, "version": "a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2" }Generated inUsing seed: 39271 Prompt: A monster in a bedroom in the style of <s0><s1> txt2img mode 0%| | 0/38 [00:00<?, ?it/s] 3%|▎ | 1/38 [00:00<00:08, 4.33it/s] 5%|▌ | 2/38 [00:00<00:08, 4.33it/s] 8%|▊ | 3/38 [00:00<00:08, 4.33it/s] 11%|█ | 4/38 [00:00<00:07, 4.33it/s] 13%|█▎ | 5/38 [00:01<00:07, 4.33it/s] 16%|█▌ | 6/38 [00:01<00:07, 4.32it/s] 18%|█▊ | 7/38 [00:01<00:07, 4.32it/s] 21%|██ | 8/38 [00:01<00:06, 4.32it/s] 24%|██▎ | 9/38 [00:02<00:06, 4.32it/s] 26%|██▋ | 10/38 [00:02<00:06, 4.32it/s] 29%|██▉ | 11/38 [00:02<00:06, 4.32it/s] 32%|███▏ | 12/38 [00:02<00:06, 4.31it/s] 34%|███▍ | 13/38 [00:03<00:05, 4.32it/s] 37%|███▋ | 14/38 [00:03<00:05, 4.31it/s] 39%|███▉ | 15/38 [00:03<00:05, 4.31it/s] 42%|████▏ | 16/38 [00:03<00:05, 4.31it/s] 45%|████▍ | 17/38 [00:03<00:04, 4.31it/s] 47%|████▋ | 18/38 [00:04<00:04, 4.31it/s] 50%|█████ | 19/38 [00:04<00:04, 4.31it/s] 53%|█████▎ | 20/38 [00:04<00:04, 4.31it/s] 55%|█████▌ | 21/38 [00:04<00:03, 4.31it/s] 58%|█████▊ | 22/38 [00:05<00:03, 4.31it/s] 61%|██████ | 23/38 [00:05<00:03, 4.31it/s] 63%|██████▎ | 24/38 [00:05<00:03, 4.31it/s] 66%|██████▌ | 25/38 [00:05<00:03, 4.31it/s] 68%|██████▊ | 26/38 [00:06<00:02, 4.31it/s] 71%|███████ | 27/38 [00:06<00:02, 4.31it/s] 74%|███████▎ | 28/38 [00:06<00:02, 4.30it/s] 76%|███████▋ | 29/38 [00:06<00:02, 4.31it/s] 79%|███████▉ | 30/38 [00:06<00:01, 4.31it/s] 82%|████████▏ | 31/38 [00:07<00:01, 4.31it/s] 84%|████████▍ | 32/38 [00:07<00:01, 4.30it/s] 87%|████████▋ | 33/38 [00:07<00:01, 4.31it/s] 89%|████████▉ | 34/38 [00:07<00:00, 4.30it/s] 92%|█████████▏| 35/38 [00:08<00:00, 4.31it/s] 95%|█████████▍| 36/38 [00:08<00:00, 4.30it/s] 97%|█████████▋| 37/38 [00:08<00:00, 4.30it/s] 100%|██████████| 38/38 [00:08<00:00, 4.30it/s] 100%|██████████| 38/38 [00:08<00:00, 4.31it/s] 0%| | 0/2 [00:00<?, ?it/s] 50%|█████ | 1/2 [00:00<00:00, 5.61it/s] 100%|██████████| 2/2 [00:00<00:00, 5.56it/s] 100%|██████████| 2/2 [00:00<00:00, 5.57it/s]Prediction
fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2IDf2ijzv3bcig6sabobtiifp5wtyStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- A photo of a monster in the style of TOK
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- prompt_strength
- 0.95
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "A photo of a monster in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "", "prompt_strength": 0.95, "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 fofr/sdxl-labyrinth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", { input: { width: 1024, height: 1024, prompt: "A photo of a monster in the style of TOK", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "", prompt_strength: 0.95, 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 fofr/sdxl-labyrinth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", input={ "width": 1024, "height": 1024, "prompt": "A photo of a monster in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "", "prompt_strength": 0.95, "num_inference_steps": 50 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-labyrinth 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": "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", "input": { "width": 1024, "height": 1024, "prompt": "A photo of a monster in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "", "prompt_strength": 0.95, "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": "2023-09-01T22:11:53.030283Z", "created_at": "2023-09-01T22:11:37.612998Z", "data_removed": false, "error": null, "id": "f2ijzv3bcig6sabobtiifp5wty", "input": { "width": 1024, "height": 1024, "prompt": "A photo of a monster in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "", "prompt_strength": 0.95, "num_inference_steps": 50 }, "logs": "Using seed: 46010\nPrompt: A photo of a monster in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/47 [00:00<?, ?it/s]\n 2%|▏ | 1/47 [00:00<00:12, 3.70it/s]\n 4%|▍ | 2/47 [00:00<00:12, 3.69it/s]\n 6%|▋ | 3/47 [00:00<00:11, 3.70it/s]\n 9%|▊ | 4/47 [00:01<00:11, 3.69it/s]\n 11%|█ | 5/47 [00:01<00:11, 3.69it/s]\n 13%|█▎ | 6/47 [00:01<00:11, 3.69it/s]\n 15%|█▍ | 7/47 [00:01<00:10, 3.69it/s]\n 17%|█▋ | 8/47 [00:02<00:10, 3.69it/s]\n 19%|█▉ | 9/47 [00:02<00:10, 3.69it/s]\n 21%|██▏ | 10/47 [00:02<00:10, 3.68it/s]\n 23%|██▎ | 11/47 [00:02<00:09, 3.68it/s]\n 26%|██▌ | 12/47 [00:03<00:09, 3.68it/s]\n 28%|██▊ | 13/47 [00:03<00:09, 3.67it/s]\n 30%|██▉ | 14/47 [00:03<00:08, 3.67it/s]\n 32%|███▏ | 15/47 [00:04<00:08, 3.67it/s]\n 34%|███▍ | 16/47 [00:04<00:08, 3.67it/s]\n 36%|███▌ | 17/47 [00:04<00:08, 3.67it/s]\n 38%|███▊ | 18/47 [00:04<00:07, 3.67it/s]\n 40%|████ | 19/47 [00:05<00:07, 3.67it/s]\n 43%|████▎ | 20/47 [00:05<00:07, 3.67it/s]\n 45%|████▍ | 21/47 [00:05<00:07, 3.67it/s]\n 47%|████▋ | 22/47 [00:05<00:06, 3.67it/s]\n 49%|████▉ | 23/47 [00:06<00:06, 3.67it/s]\n 51%|█████ | 24/47 [00:06<00:06, 3.67it/s]\n 53%|█████▎ | 25/47 [00:06<00:05, 3.67it/s]\n 55%|█████▌ | 26/47 [00:07<00:05, 3.67it/s]\n 57%|█████▋ | 27/47 [00:07<00:05, 3.67it/s]\n 60%|█████▉ | 28/47 [00:07<00:05, 3.67it/s]\n 62%|██████▏ | 29/47 [00:07<00:04, 3.67it/s]\n 64%|██████▍ | 30/47 [00:08<00:04, 3.66it/s]\n 66%|██████▌ | 31/47 [00:08<00:04, 3.67it/s]\n 68%|██████▊ | 32/47 [00:08<00:04, 3.67it/s]\n 70%|███████ | 33/47 [00:08<00:03, 3.67it/s]\n 72%|███████▏ | 34/47 [00:09<00:03, 3.66it/s]\n 74%|███████▍ | 35/47 [00:09<00:03, 3.66it/s]\n 77%|███████▋ | 36/47 [00:09<00:03, 3.66it/s]\n 79%|███████▊ | 37/47 [00:10<00:02, 3.66it/s]\n 81%|████████ | 38/47 [00:10<00:02, 3.66it/s]\n 83%|████████▎ | 39/47 [00:10<00:02, 3.66it/s]\n 85%|████████▌ | 40/47 [00:10<00:01, 3.66it/s]\n 87%|████████▋ | 41/47 [00:11<00:01, 3.66it/s]\n 89%|████████▉ | 42/47 [00:11<00:01, 3.66it/s]\n 91%|█████████▏| 43/47 [00:11<00:01, 3.66it/s]\n 94%|█████████▎| 44/47 [00:11<00:00, 3.66it/s]\n 96%|█████████▌| 45/47 [00:12<00:00, 3.66it/s]\n 98%|█████████▊| 46/47 [00:12<00:00, 3.66it/s]\n100%|██████████| 47/47 [00:12<00:00, 3.66it/s]\n100%|██████████| 47/47 [00:12<00:00, 3.67it/s]\n 0%| | 0/3 [00:00<?, ?it/s]\n 33%|███▎ | 1/3 [00:00<00:00, 4.33it/s]\n 67%|██████▋ | 2/3 [00:00<00:00, 4.32it/s]\n100%|██████████| 3/3 [00:00<00:00, 4.31it/s]\n100%|██████████| 3/3 [00:00<00:00, 4.31it/s]", "metrics": { "predict_time": 15.39895, "total_time": 15.417285 }, "output": [ "https://replicate.delivery/pbxt/V0fGfU7cTchqXUo7ALnW5WGj2kYNsm4WrKxfpzt9Q2kRdCAjA/out-0.png" ], "started_at": "2023-09-01T22:11:37.631333Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/f2ijzv3bcig6sabobtiifp5wty", "cancel": "https://api.replicate.com/v1/predictions/f2ijzv3bcig6sabobtiifp5wty/cancel" }, "version": "a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2" }Generated inUsing seed: 46010 Prompt: A photo of a monster in the style of <s0><s1> txt2img mode 0%| | 0/47 [00:00<?, ?it/s] 2%|▏ | 1/47 [00:00<00:12, 3.70it/s] 4%|▍ | 2/47 [00:00<00:12, 3.69it/s] 6%|▋ | 3/47 [00:00<00:11, 3.70it/s] 9%|▊ | 4/47 [00:01<00:11, 3.69it/s] 11%|█ | 5/47 [00:01<00:11, 3.69it/s] 13%|█▎ | 6/47 [00:01<00:11, 3.69it/s] 15%|█▍ | 7/47 [00:01<00:10, 3.69it/s] 17%|█▋ | 8/47 [00:02<00:10, 3.69it/s] 19%|█▉ | 9/47 [00:02<00:10, 3.69it/s] 21%|██▏ | 10/47 [00:02<00:10, 3.68it/s] 23%|██▎ | 11/47 [00:02<00:09, 3.68it/s] 26%|██▌ | 12/47 [00:03<00:09, 3.68it/s] 28%|██▊ | 13/47 [00:03<00:09, 3.67it/s] 30%|██▉ | 14/47 [00:03<00:08, 3.67it/s] 32%|███▏ | 15/47 [00:04<00:08, 3.67it/s] 34%|███▍ | 16/47 [00:04<00:08, 3.67it/s] 36%|███▌ | 17/47 [00:04<00:08, 3.67it/s] 38%|███▊ | 18/47 [00:04<00:07, 3.67it/s] 40%|████ | 19/47 [00:05<00:07, 3.67it/s] 43%|████▎ | 20/47 [00:05<00:07, 3.67it/s] 45%|████▍ | 21/47 [00:05<00:07, 3.67it/s] 47%|████▋ | 22/47 [00:05<00:06, 3.67it/s] 49%|████▉ | 23/47 [00:06<00:06, 3.67it/s] 51%|█████ | 24/47 [00:06<00:06, 3.67it/s] 53%|█████▎ | 25/47 [00:06<00:05, 3.67it/s] 55%|█████▌ | 26/47 [00:07<00:05, 3.67it/s] 57%|█████▋ | 27/47 [00:07<00:05, 3.67it/s] 60%|█████▉ | 28/47 [00:07<00:05, 3.67it/s] 62%|██████▏ | 29/47 [00:07<00:04, 3.67it/s] 64%|██████▍ | 30/47 [00:08<00:04, 3.66it/s] 66%|██████▌ | 31/47 [00:08<00:04, 3.67it/s] 68%|██████▊ | 32/47 [00:08<00:04, 3.67it/s] 70%|███████ | 33/47 [00:08<00:03, 3.67it/s] 72%|███████▏ | 34/47 [00:09<00:03, 3.66it/s] 74%|███████▍ | 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fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2IDd3both3b2iwpm736kzyabzjw6iStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1152
- height
- 768
- prompt
- A photo of a demon in a bedroom in the style of TOK
- refine
- expert_ensemble_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.95
- negative_prompt
- render, broken, distorted, disfigured
- prompt_strength
- 0.85
- num_inference_steps
- 40
{ "width": 1152, "height": 768, "prompt": "A photo of a demon in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "render, broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 }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 fofr/sdxl-labyrinth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", { input: { width: 1152, height: 768, prompt: "A photo of a demon in a bedroom in the style of TOK", refine: "expert_ensemble_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 1, guidance_scale: 7.5, apply_watermark: false, high_noise_frac: 0.95, negative_prompt: "render, broken, distorted, disfigured", prompt_strength: 0.85, num_inference_steps: 40 } } ); // 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 fofr/sdxl-labyrinth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", input={ "width": 1152, "height": 768, "prompt": "A photo of a demon in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": False, "high_noise_frac": 0.95, "negative_prompt": "render, broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run fofr/sdxl-labyrinth 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": "fofr/sdxl-labyrinth:a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2", "input": { "width": 1152, "height": 768, "prompt": "A photo of a demon in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "render, broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-09-01T22:17:34.367029Z", "created_at": "2023-09-01T22:17:23.332533Z", "data_removed": false, "error": null, "id": "d3both3b2iwpm736kzyabzjw6i", "input": { "width": 1152, "height": 768, "prompt": "A photo of a demon in a bedroom in the style of TOK", "refine": "expert_ensemble_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 1, "guidance_scale": 7.5, "apply_watermark": false, "high_noise_frac": 0.95, "negative_prompt": "render, broken, distorted, disfigured", "prompt_strength": 0.85, "num_inference_steps": 40 }, "logs": "Using seed: 19334\nPrompt: A photo of a demon in a bedroom in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/38 [00:00<?, ?it/s]\n 3%|▎ | 1/38 [00:00<00:08, 4.34it/s]\n 5%|▌ | 2/38 [00:00<00:08, 4.33it/s]\n 8%|▊ | 3/38 [00:00<00:08, 4.33it/s]\n 11%|█ | 4/38 [00:00<00:07, 4.33it/s]\n 13%|█▎ | 5/38 [00:01<00:07, 4.32it/s]\n 16%|█▌ | 6/38 [00:01<00:07, 4.32it/s]\n 18%|█▊ | 7/38 [00:01<00:07, 4.32it/s]\n 21%|██ | 8/38 [00:01<00:06, 4.32it/s]\n 24%|██▎ | 9/38 [00:02<00:06, 4.32it/s]\n 26%|██▋ | 10/38 [00:02<00:06, 4.32it/s]\n 29%|██▉ | 11/38 [00:02<00:06, 4.32it/s]\n 32%|███▏ | 12/38 [00:02<00:06, 4.32it/s]\n 34%|███▍ | 13/38 [00:03<00:05, 4.32it/s]\n 37%|███▋ | 14/38 [00:03<00:05, 4.32it/s]\n 39%|███▉ | 15/38 [00:03<00:05, 4.32it/s]\n 42%|████▏ | 16/38 [00:03<00:05, 4.32it/s]\n 45%|████▍ | 17/38 [00:03<00:04, 4.32it/s]\n 47%|████▋ | 18/38 [00:04<00:04, 4.30it/s]\n 50%|█████ | 19/38 [00:04<00:04, 4.30it/s]\n 53%|█████▎ | 20/38 [00:04<00:04, 4.30it/s]\n 55%|█████▌ | 21/38 [00:04<00:03, 4.30it/s]\n 58%|█████▊ | 22/38 [00:05<00:03, 4.30it/s]\n 61%|██████ | 23/38 [00:05<00:03, 4.30it/s]\n 63%|██████▎ | 24/38 [00:05<00:03, 4.30it/s]\n 66%|██████▌ | 25/38 [00:05<00:03, 4.30it/s]\n 68%|██████▊ | 26/38 [00:06<00:02, 4.30it/s]\n 71%|███████ | 27/38 [00:06<00:02, 4.30it/s]\n 74%|███████▎ | 28/38 [00:06<00:02, 4.30it/s]\n 76%|███████▋ | 29/38 [00:06<00:02, 4.31it/s]\n 79%|███████▉ | 30/38 [00:06<00:01, 4.30it/s]\n 82%|████████▏ | 31/38 [00:07<00:01, 4.30it/s]\n 84%|████████▍ | 32/38 [00:07<00:01, 4.30it/s]\n 87%|████████▋ | 33/38 [00:07<00:01, 4.30it/s]\n 89%|████████▉ | 34/38 [00:07<00:00, 4.29it/s]\n 92%|█████████▏| 35/38 [00:08<00:00, 4.30it/s]\n 95%|█████████▍| 36/38 [00:08<00:00, 4.29it/s]\n 97%|█████████▋| 37/38 [00:08<00:00, 4.29it/s]\n100%|██████████| 38/38 [00:08<00:00, 4.30it/s]\n100%|██████████| 38/38 [00:08<00:00, 4.31it/s]\n 0%| | 0/2 [00:00<?, ?it/s]\n 50%|█████ | 1/2 [00:00<00:00, 5.60it/s]\n100%|██████████| 2/2 [00:00<00:00, 5.55it/s]\n100%|██████████| 2/2 [00:00<00:00, 5.56it/s]", "metrics": { "predict_time": 11.032898, "total_time": 11.034496 }, "output": [ "https://replicate.delivery/pbxt/dMEIl2FbIBofTa35Nddi30JtW9lmqDji0ll7eInVWeu6nCAjA/out-0.png" ], "started_at": "2023-09-01T22:17:23.334131Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d3both3b2iwpm736kzyabzjw6i", "cancel": "https://api.replicate.com/v1/predictions/d3both3b2iwpm736kzyabzjw6i/cancel" }, "version": "a95510c9f58c973633edd21fd871312505612991d1f7253db44519914bf680a2" }Generated inUsing seed: 19334 Prompt: A photo of a demon in a bedroom in the style of <s0><s1> txt2img mode 0%| | 0/38 [00:00<?, ?it/s] 3%|▎ | 1/38 [00:00<00:08, 4.34it/s] 5%|▌ | 2/38 [00:00<00:08, 4.33it/s] 8%|▊ | 3/38 [00:00<00:08, 4.33it/s] 11%|█ | 4/38 [00:00<00:07, 4.33it/s] 13%|█▎ | 5/38 [00:01<00:07, 4.32it/s] 16%|█▌ | 6/38 [00:01<00:07, 4.32it/s] 18%|█▊ | 7/38 [00:01<00:07, 4.32it/s] 21%|██ | 8/38 [00:01<00:06, 4.32it/s] 24%|██▎ | 9/38 [00:02<00:06, 4.32it/s] 26%|██▋ | 10/38 [00:02<00:06, 4.32it/s] 29%|██▉ | 11/38 [00:02<00:06, 4.32it/s] 32%|███▏ | 12/38 [00:02<00:06, 4.32it/s] 34%|███▍ | 13/38 [00:03<00:05, 4.32it/s] 37%|███▋ | 14/38 [00:03<00:05, 4.32it/s] 39%|███▉ | 15/38 [00:03<00:05, 4.32it/s] 42%|████▏ | 16/38 [00:03<00:05, 4.32it/s] 45%|████▍ | 17/38 [00:03<00:04, 4.32it/s] 47%|████▋ | 18/38 [00:04<00:04, 4.30it/s] 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5.60it/s] 100%|██████████| 2/2 [00:00<00:00, 5.55it/s] 100%|██████████| 2/2 [00:00<00:00, 5.56it/s]
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