cbh123 / sdxl-illusions
- Public
- 251 runs
-
L40S
Prediction
cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641acIDsuj3nldbxdeozvvgffvc5us7xaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- an image in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "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, "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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", { input: { width: 1024, height: 1024, prompt: "an image in the style of TOK", 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, 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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", input={ "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "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, "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 cbh123/sdxl-illusions 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": "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", "input": { "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "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, "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": "2023-08-22T20:20:51.850562Z", "created_at": "2023-08-22T20:19:18.030682Z", "data_removed": false, "error": null, "id": "suj3nldbxdeozvvgffvc5us7xa", "input": { "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "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, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 9595\nPrompt: an image in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:41, 1.18it/s]\n 4%|▍ | 2/50 [00:01<00:24, 1.96it/s]\n 6%|▌ | 3/50 [00:01<00:18, 2.49it/s]\n 8%|▊ | 4/50 [00:01<00:16, 2.86it/s]\n 10%|█ | 5/50 [00:01<00:14, 3.10it/s]\n 12%|█▏ | 6/50 [00:02<00:13, 3.27it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.39it/s]\n 16%|█▌ | 8/50 [00:02<00:12, 3.47it/s]\n 18%|█▊ | 9/50 [00:03<00:11, 3.53it/s]\n 20%|██ | 10/50 [00:03<00:11, 3.57it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.60it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.63it/s]\n 26%|██▌ | 13/50 [00:04<00:10, 3.64it/s]\n 28%|██▊ | 14/50 [00:04<00:09, 3.65it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.66it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.67it/s]\n 34%|███▍ | 17/50 [00:05<00:08, 3.67it/s]\n 36%|███▌ | 18/50 [00:05<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:06<00:08, 3.68it/s]\n 42%|████▏ | 21/50 [00:06<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:06<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s]\n 48%|████▊ | 24/50 [00:07<00:07, 3.68it/s]\n 50%|█████ | 25/50 [00:07<00:06, 3.68it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.68it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s]\n 56%|█████▌ | 28/50 [00:08<00:05, 3.68it/s]\n 58%|█████▊ | 29/50 [00:08<00:05, 3.68it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.68it/s]\n 62%|██████▏ | 31/50 [00:09<00:05, 3.68it/s]\n 64%|██████▍ | 32/50 [00:09<00:04, 3.68it/s]\n 66%|██████▌ | 33/50 [00:09<00:04, 3.68it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.67it/s]\n 70%|███████ | 35/50 [00:10<00:04, 3.67it/s]\n 72%|███████▏ | 36/50 [00:10<00:03, 3.67it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s]\n 78%|███████▊ | 39/50 [00:11<00:02, 3.67it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:12<00:02, 3.67it/s]\n 86%|████████▌ | 43/50 [00:12<00:01, 3.67it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s]\n 92%|█████████▏| 46/50 [00:13<00:01, 3.66it/s]\n 94%|█████████▍| 47/50 [00:13<00:00, 3.66it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.66it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.66it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.66it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.52it/s]", "metrics": { "predict_time": 16.804614, "total_time": 93.81988 }, "output": [ "https://replicate.delivery/pbxt/DZeZnhZYh90YZKveyzC1IRnmzfoERHLRq0qRoGBdxoEFVZ5iA/out-0.png" ], "started_at": "2023-08-22T20:20:35.045948Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/suj3nldbxdeozvvgffvc5us7xa", "cancel": "https://api.replicate.com/v1/predictions/suj3nldbxdeozvvgffvc5us7xa/cancel" }, "version": "4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac" }Generated inUsing seed: 9595 Prompt: an image in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:41, 1.18it/s] 4%|▍ | 2/50 [00:01<00:24, 1.96it/s] 6%|▌ | 3/50 [00:01<00:18, 2.49it/s] 8%|▊ | 4/50 [00:01<00:16, 2.86it/s] 10%|█ | 5/50 [00:01<00:14, 3.10it/s] 12%|█▏ | 6/50 [00:02<00:13, 3.27it/s] 14%|█▍ | 7/50 [00:02<00:12, 3.39it/s] 16%|█▌ | 8/50 [00:02<00:12, 3.47it/s] 18%|█▊ | 9/50 [00:03<00:11, 3.53it/s] 20%|██ | 10/50 [00:03<00:11, 3.57it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.60it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.63it/s] 26%|██▌ | 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3.67it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s] 78%|███████▊ | 39/50 [00:11<00:02, 3.67it/s] 80%|████████ | 40/50 [00:11<00:02, 3.67it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s] 84%|████████▍ | 42/50 [00:12<00:02, 3.67it/s] 86%|████████▌ | 43/50 [00:12<00:01, 3.67it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.67it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s] 92%|█████████▏| 46/50 [00:13<00:01, 3.66it/s] 94%|█████████▍| 47/50 [00:13<00:00, 3.66it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.66it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.66it/s] 100%|██████████| 50/50 [00:14<00:00, 3.66it/s] 100%|██████████| 50/50 [00:14<00:00, 3.52it/s]Prediction
cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641acID5iwc2idbgubkp4kg6eqyxwe5oaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- an optical illusion in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", { input: { width: 1024, height: 1024, prompt: "an optical illusion in the style of TOK", 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, 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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", input={ "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "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 cbh123/sdxl-illusions 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": "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", "input": { "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "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": "2023-08-22T20:23:57.564907Z", "created_at": "2023-08-22T20:23:42.550732Z", "data_removed": false, "error": null, "id": "5iwc2idbgubkp4kg6eqyxwe5oa", "input": { "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 17393\nPrompt: an optical illusion in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.68it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.68it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.68it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.68it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.68it/s]\n 12%|█▏ | 6/50 [00:01<00:11, 3.68it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.68it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.68it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.68it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.67it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.67it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.67it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.67it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.67it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.67it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.66it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.66it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.66it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.66it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.66it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.66it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.66it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.66it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.66it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.66it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.66it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.66it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.66it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.66it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.66it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.66it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.66it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.65it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.65it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.65it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.65it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]", "metrics": { "predict_time": 15.044671, "total_time": 15.014175 }, "output": [ "https://replicate.delivery/pbxt/f9AxdRmyPH1gdyBmIWaMm6xQOZpc74N42kY6xJwbcajuWWuIA/out-0.png" ], "started_at": "2023-08-22T20:23:42.520236Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/5iwc2idbgubkp4kg6eqyxwe5oa", "cancel": "https://api.replicate.com/v1/predictions/5iwc2idbgubkp4kg6eqyxwe5oa/cancel" }, "version": "4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac" }Generated inUsing seed: 17393 Prompt: an optical illusion in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.68it/s] 4%|▍ | 2/50 [00:00<00:13, 3.68it/s] 6%|▌ | 3/50 [00:00<00:12, 3.68it/s] 8%|▊ | 4/50 [00:01<00:12, 3.68it/s] 10%|█ | 5/50 [00:01<00:12, 3.68it/s] 12%|█▏ | 6/50 [00:01<00:11, 3.68it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.68it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.68it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s] 20%|██ | 10/50 [00:02<00:10, 3.68it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.68it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.67it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.67it/s] 30%|███ | 15/50 [00:04<00:09, 3.67it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.67it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.67it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.67it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.66it/s] 40%|████ | 20/50 [00:05<00:08, 3.66it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.66it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.66it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.66it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.66it/s] 50%|█████ | 25/50 [00:06<00:06, 3.66it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.66it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.66it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s] 60%|██████ | 30/50 [00:08<00:05, 3.66it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.66it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.66it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s] 70%|███████ | 35/50 [00:09<00:04, 3.66it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.66it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.66it/s] 80%|████████ | 40/50 [00:10<00:02, 3.66it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.66it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.66it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.65it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.65it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.65it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.65it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s] 100%|██████████| 50/50 [00:13<00:00, 3.65it/s] 100%|██████████| 50/50 [00:13<00:00, 3.66it/s]Prediction
cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641acID52qekylbanr5iiedxr2jdos7ueStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- an optical illusion in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", { input: { width: 1024, height: 1024, prompt: "an optical illusion in the style of TOK", 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, 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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", input={ "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "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 cbh123/sdxl-illusions 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": "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", "input": { "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "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": "2023-08-22T20:34:07.211735Z", "created_at": "2023-08-22T20:33:52.284676Z", "data_removed": false, "error": null, "id": "52qekylbanr5iiedxr2jdos7ue", "input": { "width": 1024, "height": 1024, "prompt": "an optical illusion in the style of TOK", "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, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 8938\nPrompt: an optical illusion in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.69it/s]\n 4%|▍ | 2/50 [00:00<00:13, 3.68it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.67it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.66it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.66it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.67it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.67it/s]\n 22%|██▏ | 11/50 [00:02<00:10, 3.67it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.67it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.67it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.67it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.67it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.67it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.67it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.67it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.67it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.67it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.67it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.67it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.67it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.67it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s]\n 56%|█████▌ | 28/50 [00:07<00:06, 3.67it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.66it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.66it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.66it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.66it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.66it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s]\n 78%|███████▊ | 39/50 [00:10<00:03, 3.66it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.66it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.66it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s]\n 88%|████████▊ | 44/50 [00:12<00:01, 3.66it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.66it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.66it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.65it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.65it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.65it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]", "metrics": { "predict_time": 15.067815, "total_time": 14.927059 }, "output": [ "https://replicate.delivery/pbxt/AXOsBtHZuLLsElabaj8ZkbHORoZpCfoSU6mfpNJwzRretZ5iA/out-0.png" ], "started_at": "2023-08-22T20:33:52.143920Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/52qekylbanr5iiedxr2jdos7ue", "cancel": "https://api.replicate.com/v1/predictions/52qekylbanr5iiedxr2jdos7ue/cancel" }, "version": "4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac" }Generated inUsing seed: 8938 Prompt: an optical illusion in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.69it/s] 4%|▍ | 2/50 [00:00<00:13, 3.68it/s] 6%|▌ | 3/50 [00:00<00:12, 3.67it/s] 8%|▊ | 4/50 [00:01<00:12, 3.66it/s] 10%|█ | 5/50 [00:01<00:12, 3.66it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.66it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.67it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.67it/s] 20%|██ | 10/50 [00:02<00:10, 3.67it/s] 22%|██▏ | 11/50 [00:02<00:10, 3.67it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s] 26%|██▌ | 13/50 [00:03<00:10, 3.67it/s] 28%|██▊ | 14/50 [00:03<00:09, 3.67it/s] 30%|███ | 15/50 [00:04<00:09, 3.67it/s] 32%|███▏ | 16/50 [00:04<00:09, 3.67it/s] 34%|███▍ | 17/50 [00:04<00:08, 3.67it/s] 36%|███▌ | 18/50 [00:04<00:08, 3.67it/s] 38%|███▊ | 19/50 [00:05<00:08, 3.67it/s] 40%|████ | 20/50 [00:05<00:08, 3.67it/s] 42%|████▏ | 21/50 [00:05<00:07, 3.67it/s] 44%|████▍ | 22/50 [00:05<00:07, 3.67it/s] 46%|████▌ | 23/50 [00:06<00:07, 3.67it/s] 48%|████▊ | 24/50 [00:06<00:07, 3.67it/s] 50%|█████ | 25/50 [00:06<00:06, 3.67it/s] 52%|█████▏ | 26/50 [00:07<00:06, 3.66it/s] 54%|█████▍ | 27/50 [00:07<00:06, 3.67it/s] 56%|█████▌ | 28/50 [00:07<00:06, 3.67it/s] 58%|█████▊ | 29/50 [00:07<00:05, 3.66it/s] 60%|██████ | 30/50 [00:08<00:05, 3.66it/s] 62%|██████▏ | 31/50 [00:08<00:05, 3.66it/s] 64%|██████▍ | 32/50 [00:08<00:04, 3.66it/s] 66%|██████▌ | 33/50 [00:08<00:04, 3.66it/s] 68%|██████▊ | 34/50 [00:09<00:04, 3.66it/s] 70%|███████ | 35/50 [00:09<00:04, 3.66it/s] 72%|███████▏ | 36/50 [00:09<00:03, 3.66it/s] 74%|███████▍ | 37/50 [00:10<00:03, 3.66it/s] 76%|███████▌ | 38/50 [00:10<00:03, 3.66it/s] 78%|███████▊ | 39/50 [00:10<00:03, 3.66it/s] 80%|████████ | 40/50 [00:10<00:02, 3.66it/s] 82%|████████▏ | 41/50 [00:11<00:02, 3.66it/s] 84%|████████▍ | 42/50 [00:11<00:02, 3.66it/s] 86%|████████▌ | 43/50 [00:11<00:01, 3.66it/s] 88%|████████▊ | 44/50 [00:12<00:01, 3.66it/s] 90%|█████████ | 45/50 [00:12<00:01, 3.66it/s] 92%|█████████▏| 46/50 [00:12<00:01, 3.66it/s] 94%|█████████▍| 47/50 [00:12<00:00, 3.65it/s] 96%|█████████▌| 48/50 [00:13<00:00, 3.65it/s] 98%|█████████▊| 49/50 [00:13<00:00, 3.65it/s] 100%|██████████| 50/50 [00:13<00:00, 3.65it/s] 100%|██████████| 50/50 [00:13<00:00, 3.66it/s]Prediction
cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641acIDkwx7u5dbuotz6opreh6ufssrvqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- an image in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 4
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", { input: { width: 1024, height: 1024, prompt: "an image in the style of TOK", refine: "no_refiner", scheduler: "K_EULER", lora_scale: 0.6, num_outputs: 4, guidance_scale: 7.5, apply_watermark: true, high_noise_frac: 0.8, 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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", input={ "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": True, "high_noise_frac": 0.8, "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 cbh123/sdxl-illusions 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": "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", "input": { "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "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": "2023-08-22T20:22:51.360315Z", "created_at": "2023-08-22T20:21:54.903985Z", "data_removed": false, "error": null, "id": "kwx7u5dbuotz6opreh6ufssrvq", "input": { "width": 1024, "height": 1024, "prompt": "an image in the style of TOK", "refine": "no_refiner", "scheduler": "K_EULER", "lora_scale": 0.6, "num_outputs": 4, "guidance_scale": 7.5, "apply_watermark": true, "high_noise_frac": 0.8, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 22387\nPrompt: an image in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:01<00:49, 1.01s/it]\n 4%|▍ | 2/50 [00:02<00:48, 1.01s/it]\n 6%|▌ | 3/50 [00:03<00:47, 1.01s/it]\n 8%|▊ | 4/50 [00:04<00:46, 1.01s/it]\n 10%|█ | 5/50 [00:05<00:45, 1.01s/it]\n 12%|█▏ | 6/50 [00:06<00:44, 1.01s/it]\n 14%|█▍ | 7/50 [00:07<00:43, 1.01s/it]\n 16%|█▌ | 8/50 [00:08<00:42, 1.01s/it]\n 18%|█▊ | 9/50 [00:09<00:41, 1.01s/it]\n 20%|██ | 10/50 [00:10<00:40, 1.01s/it]\n 22%|██▏ | 11/50 [00:11<00:39, 1.01s/it]\n 24%|██▍ | 12/50 [00:12<00:38, 1.01s/it]\n 26%|██▌ | 13/50 [00:13<00:37, 1.01s/it]\n 28%|██▊ | 14/50 [00:14<00:36, 1.01s/it]\n 30%|███ | 15/50 [00:15<00:35, 1.01s/it]\n 32%|███▏ | 16/50 [00:16<00:34, 1.01s/it]\n 34%|███▍ | 17/50 [00:17<00:33, 1.01s/it]\n 36%|███▌ | 18/50 [00:18<00:32, 1.01s/it]\n 38%|███▊ | 19/50 [00:19<00:31, 1.01s/it]\n 40%|████ | 20/50 [00:20<00:30, 1.01s/it]\n 42%|████▏ | 21/50 [00:21<00:29, 1.01s/it]\n 44%|████▍ | 22/50 [00:22<00:28, 1.01s/it]\n 46%|████▌ | 23/50 [00:23<00:27, 1.01s/it]\n 48%|████▊ | 24/50 [00:24<00:26, 1.01s/it]\n 50%|█████ | 25/50 [00:25<00:25, 1.01s/it]\n 52%|█████▏ | 26/50 [00:26<00:24, 1.01s/it]\n 54%|█████▍ | 27/50 [00:27<00:23, 1.01s/it]\n 56%|█████▌ | 28/50 [00:28<00:22, 1.01s/it]\n 58%|█████▊ | 29/50 [00:29<00:21, 1.01s/it]\n 60%|██████ | 30/50 [00:30<00:20, 1.01s/it]\n 62%|██████▏ | 31/50 [00:31<00:19, 1.01s/it]\n 64%|██████▍ | 32/50 [00:32<00:18, 1.01s/it]\n 66%|██████▌ | 33/50 [00:33<00:17, 1.01s/it]\n 68%|██████▊ | 34/50 [00:34<00:16, 1.01s/it]\n 70%|███████ | 35/50 [00:35<00:15, 1.01s/it]\n 72%|███████▏ | 36/50 [00:36<00:14, 1.01s/it]\n 74%|███████▍ | 37/50 [00:37<00:13, 1.01s/it]\n 76%|███████▌ | 38/50 [00:38<00:12, 1.01s/it]\n 78%|███████▊ | 39/50 [00:39<00:11, 1.01s/it]\n 80%|████████ | 40/50 [00:40<00:10, 1.01s/it]\n 82%|████████▏ | 41/50 [00:41<00:09, 1.01s/it]\n 84%|████████▍ | 42/50 [00:42<00:08, 1.01s/it]\n 86%|████████▌ | 43/50 [00:43<00:07, 1.01s/it]\n 88%|████████▊ | 44/50 [00:44<00:06, 1.01s/it]\n 90%|█████████ | 45/50 [00:45<00:05, 1.01s/it]\n 92%|█████████▏| 46/50 [00:46<00:04, 1.01s/it]\n 94%|█████████▍| 47/50 [00:47<00:03, 1.01s/it]\n 96%|█████████▌| 48/50 [00:48<00:02, 1.01s/it]\n 98%|█████████▊| 49/50 [00:49<00:01, 1.01s/it]\n100%|██████████| 50/50 [00:50<00:00, 1.01s/it]\n100%|██████████| 50/50 [00:50<00:00, 1.01s/it]", "metrics": { "predict_time": 56.479056, "total_time": 56.45633 }, "output": [ "https://replicate.delivery/pbxt/hzkjAW54u9ohCZhllFVywIfnwMtSQelyuzMJCs0cBXOZsscRA/out-0.png", "https://replicate.delivery/pbxt/PbZOaIdPOXLVIdquJIVeZSBWk4c0Y1cgHKHFa6yNla2MWWuIA/out-1.png", "https://replicate.delivery/pbxt/asl4M0PpMkqVBdc1f2GjJ1fhtNWymWck0FC9oiCKNNtasscRA/out-2.png", "https://replicate.delivery/pbxt/9NBRynjfpH1HPiPMHzh270FpH0nffxcp07zNv2KyCXB1YZ5iA/out-3.png" ], "started_at": "2023-08-22T20:21:54.881259Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/kwx7u5dbuotz6opreh6ufssrvq", "cancel": "https://api.replicate.com/v1/predictions/kwx7u5dbuotz6opreh6ufssrvq/cancel" }, "version": "4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac" }Generated inUsing seed: 22387 Prompt: an image in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:01<00:49, 1.01s/it] 4%|▍ | 2/50 [00:02<00:48, 1.01s/it] 6%|▌ | 3/50 [00:03<00:47, 1.01s/it] 8%|▊ | 4/50 [00:04<00:46, 1.01s/it] 10%|█ | 5/50 [00:05<00:45, 1.01s/it] 12%|█▏ | 6/50 [00:06<00:44, 1.01s/it] 14%|█▍ | 7/50 [00:07<00:43, 1.01s/it] 16%|█▌ | 8/50 [00:08<00:42, 1.01s/it] 18%|█▊ | 9/50 [00:09<00:41, 1.01s/it] 20%|██ | 10/50 [00:10<00:40, 1.01s/it] 22%|██▏ | 11/50 [00:11<00:39, 1.01s/it] 24%|██▍ | 12/50 [00:12<00:38, 1.01s/it] 26%|██▌ | 13/50 [00:13<00:37, 1.01s/it] 28%|██▊ | 14/50 [00:14<00:36, 1.01s/it] 30%|███ | 15/50 [00:15<00:35, 1.01s/it] 32%|███▏ | 16/50 [00:16<00:34, 1.01s/it] 34%|███▍ | 17/50 [00:17<00:33, 1.01s/it] 36%|███▌ | 18/50 [00:18<00:32, 1.01s/it] 38%|███▊ | 19/50 [00:19<00:31, 1.01s/it] 40%|████ | 20/50 [00:20<00:30, 1.01s/it] 42%|████▏ | 21/50 [00:21<00:29, 1.01s/it] 44%|████▍ | 22/50 [00:22<00:28, 1.01s/it] 46%|████▌ | 23/50 [00:23<00:27, 1.01s/it] 48%|████▊ | 24/50 [00:24<00:26, 1.01s/it] 50%|█████ | 25/50 [00:25<00:25, 1.01s/it] 52%|█████▏ | 26/50 [00:26<00:24, 1.01s/it] 54%|█████▍ | 27/50 [00:27<00:23, 1.01s/it] 56%|█████▌ | 28/50 [00:28<00:22, 1.01s/it] 58%|█████▊ | 29/50 [00:29<00:21, 1.01s/it] 60%|██████ | 30/50 [00:30<00:20, 1.01s/it] 62%|██████▏ | 31/50 [00:31<00:19, 1.01s/it] 64%|██████▍ | 32/50 [00:32<00:18, 1.01s/it] 66%|██████▌ | 33/50 [00:33<00:17, 1.01s/it] 68%|██████▊ | 34/50 [00:34<00:16, 1.01s/it] 70%|███████ | 35/50 [00:35<00:15, 1.01s/it] 72%|███████▏ | 36/50 [00:36<00:14, 1.01s/it] 74%|███████▍ | 37/50 [00:37<00:13, 1.01s/it] 76%|███████▌ | 38/50 [00:38<00:12, 1.01s/it] 78%|███████▊ | 39/50 [00:39<00:11, 1.01s/it] 80%|████████ | 40/50 [00:40<00:10, 1.01s/it] 82%|████████▏ | 41/50 [00:41<00:09, 1.01s/it] 84%|████████▍ | 42/50 [00:42<00:08, 1.01s/it] 86%|████████▌ | 43/50 [00:43<00:07, 1.01s/it] 88%|████████▊ | 44/50 [00:44<00:06, 1.01s/it] 90%|█████████ | 45/50 [00:45<00:05, 1.01s/it] 92%|█████████▏| 46/50 [00:46<00:04, 1.01s/it] 94%|█████████▍| 47/50 [00:47<00:03, 1.01s/it] 96%|█████████▌| 48/50 [00:48<00:02, 1.01s/it] 98%|█████████▊| 49/50 [00:49<00:01, 1.01s/it] 100%|██████████| 50/50 [00:50<00:00, 1.01s/it] 100%|██████████| 50/50 [00:50<00:00, 1.01s/it]Prediction
cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641acID7ntm723bsmitkfx63pssnm5b5yStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 1024
- height
- 1024
- prompt
- a painting in the style of TOK
- refine
- no_refiner
- scheduler
- K_EULER
- lora_scale
- 0.6
- num_outputs
- 1
- guidance_scale
- 7.5
- apply_watermark
- high_noise_frac
- 0.8
- prompt_strength
- 0.8
- num_inference_steps
- 50
{ "width": 1024, "height": 1024, "prompt": "a painting in the style of TOK", "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, "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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", { input: { width: 1024, height: 1024, prompt: "a painting in the style of TOK", 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, 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 cbh123/sdxl-illusions using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", input={ "width": 1024, "height": 1024, "prompt": "a painting in the style of TOK", "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, "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 cbh123/sdxl-illusions 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": "cbh123/sdxl-illusions:4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac", "input": { "width": 1024, "height": 1024, "prompt": "a painting in the style of TOK", "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, "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": "2023-08-22T20:27:36.360091Z", "created_at": "2023-08-22T20:27:21.344261Z", "data_removed": false, "error": null, "id": "7ntm723bsmitkfx63pssnm5b5y", "input": { "width": 1024, "height": 1024, "prompt": "a painting in the style of TOK", "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, "prompt_strength": 0.8, "num_inference_steps": 50 }, "logs": "Using seed: 53938\nPrompt: a painting in the style of <s0><s1>\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:13, 3.70it/s]\n 4%|▍ | 2/50 [00:00<00:12, 3.70it/s]\n 6%|▌ | 3/50 [00:00<00:12, 3.69it/s]\n 8%|▊ | 4/50 [00:01<00:12, 3.66it/s]\n 10%|█ | 5/50 [00:01<00:12, 3.66it/s]\n 12%|█▏ | 6/50 [00:01<00:12, 3.67it/s]\n 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s]\n 16%|█▌ | 8/50 [00:02<00:11, 3.66it/s]\n 18%|█▊ | 9/50 [00:02<00:11, 3.66it/s]\n 20%|██ | 10/50 [00:02<00:10, 3.66it/s]\n 22%|██▏ | 11/50 [00:03<00:10, 3.66it/s]\n 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s]\n 26%|██▌ | 13/50 [00:03<00:10, 3.67it/s]\n 28%|██▊ | 14/50 [00:03<00:09, 3.67it/s]\n 30%|███ | 15/50 [00:04<00:09, 3.67it/s]\n 32%|███▏ | 16/50 [00:04<00:09, 3.68it/s]\n 34%|███▍ | 17/50 [00:04<00:08, 3.68it/s]\n 36%|███▌ | 18/50 [00:04<00:08, 3.68it/s]\n 38%|███▊ | 19/50 [00:05<00:08, 3.68it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.68it/s]\n 42%|████▏ | 21/50 [00:05<00:07, 3.68it/s]\n 44%|████▍ | 22/50 [00:05<00:07, 3.68it/s]\n 46%|████▌ | 23/50 [00:06<00:07, 3.68it/s]\n 48%|████▊ | 24/50 [00:06<00:07, 3.67it/s]\n 50%|█████ | 25/50 [00:06<00:06, 3.67it/s]\n 52%|█████▏ | 26/50 [00:07<00:06, 3.67it/s]\n 54%|█████▍ | 27/50 [00:07<00:06, 3.68it/s]\n 56%|█████▌ | 28/50 [00:07<00:05, 3.67it/s]\n 58%|█████▊ | 29/50 [00:07<00:05, 3.67it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.67it/s]\n 62%|██████▏ | 31/50 [00:08<00:05, 3.67it/s]\n 64%|██████▍ | 32/50 [00:08<00:04, 3.67it/s]\n 66%|██████▌ | 33/50 [00:08<00:04, 3.67it/s]\n 68%|██████▊ | 34/50 [00:09<00:04, 3.67it/s]\n 70%|███████ | 35/50 [00:09<00:04, 3.67it/s]\n 72%|███████▏ | 36/50 [00:09<00:03, 3.67it/s]\n 74%|███████▍ | 37/50 [00:10<00:03, 3.67it/s]\n 76%|███████▌ | 38/50 [00:10<00:03, 3.67it/s]\n 78%|███████▊ | 39/50 [00:10<00:02, 3.67it/s]\n 80%|████████ | 40/50 [00:10<00:02, 3.67it/s]\n 82%|████████▏ | 41/50 [00:11<00:02, 3.67it/s]\n 84%|████████▍ | 42/50 [00:11<00:02, 3.67it/s]\n 86%|████████▌ | 43/50 [00:11<00:01, 3.67it/s]\n 88%|████████▊ | 44/50 [00:11<00:01, 3.67it/s]\n 90%|█████████ | 45/50 [00:12<00:01, 3.67it/s]\n 92%|█████████▏| 46/50 [00:12<00:01, 3.67it/s]\n 94%|█████████▍| 47/50 [00:12<00:00, 3.67it/s]\n 96%|█████████▌| 48/50 [00:13<00:00, 3.66it/s]\n 98%|█████████▊| 49/50 [00:13<00:00, 3.67it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.66it/s]\n100%|██████████| 50/50 [00:13<00:00, 3.67it/s]", "metrics": { "predict_time": 15.051705, "total_time": 15.01583 }, "output": [ "https://replicate.delivery/pbxt/Q903GiyXG3LjH9SRUmLfMz1OZHNS3xtTOvfjHkWfs8xvhZ5iA/out-0.png" ], "started_at": "2023-08-22T20:27:21.308386Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/7ntm723bsmitkfx63pssnm5b5y", "cancel": "https://api.replicate.com/v1/predictions/7ntm723bsmitkfx63pssnm5b5y/cancel" }, "version": "4d3491c45be12fae0972e28a55ea146cef41b717883641fcd46c60fbfc9641ac" }Generated inUsing seed: 53938 Prompt: a painting in the style of <s0><s1> txt2img mode 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:00<00:13, 3.70it/s] 4%|▍ | 2/50 [00:00<00:12, 3.70it/s] 6%|▌ | 3/50 [00:00<00:12, 3.69it/s] 8%|▊ | 4/50 [00:01<00:12, 3.66it/s] 10%|█ | 5/50 [00:01<00:12, 3.66it/s] 12%|█▏ | 6/50 [00:01<00:12, 3.67it/s] 14%|█▍ | 7/50 [00:01<00:11, 3.66it/s] 16%|█▌ | 8/50 [00:02<00:11, 3.66it/s] 18%|█▊ | 9/50 [00:02<00:11, 3.66it/s] 20%|██ | 10/50 [00:02<00:10, 3.66it/s] 22%|██▏ | 11/50 [00:03<00:10, 3.66it/s] 24%|██▍ | 12/50 [00:03<00:10, 3.67it/s] 26%|██▌ | 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