chenxwh / meissonic
Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
Prediction
chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDxmnt06t0dsrgj0cjndkv7try1cStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- a photo of an astronaut riding a horse on mars
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "a photo of an astronaut riding a horse on mars", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "a photo of an astronaut riding a horse on mars", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "a photo of an astronaut riding a horse on mars", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "a photo of an astronaut riding a horse on mars", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:31:33.131320Z", "created_at": "2024-10-20T19:28:43.630000Z", "data_removed": false, "error": null, "id": "xmnt06t0dsrgj0cjndkv7try1c", "input": { "prompt": "a photo of an astronaut riding a horse on mars", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 43882\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:31, 2.02it/s]\n 3%|▎ | 2/64 [00:00<00:21, 2.94it/s]\n 5%|▍ | 3/64 [00:00<00:17, 3.43it/s]\n 6%|▋ | 4/64 [00:01<00:16, 3.72it/s]\n 8%|▊ | 5/64 [00:01<00:15, 3.90it/s]\n 9%|▉ | 6/64 [00:01<00:14, 4.02it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.10it/s]\n 12%|█▎ | 8/64 [00:02<00:13, 4.16it/s]\n 14%|█▍ | 9/64 [00:02<00:13, 4.19it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.22it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.24it/s]\n 19%|█▉ | 12/64 [00:03<00:12, 4.25it/s]\n 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[00:13<00:01, 4.25it/s]\n 91%|█████████ | 58/64 [00:14<00:01, 4.25it/s]\n 92%|█████████▏| 59/64 [00:14<00:01, 4.24it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.24it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.24it/s]\n 97%|█████████▋| 62/64 [00:15<00:00, 4.23it/s]\n 98%|█████████▊| 63/64 [00:15<00:00, 4.24it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.25it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.11it/s]", "metrics": { "predict_time": 18.370107867, "total_time": 169.50132 }, "output": "https://replicate.delivery/pbxt/tWEHQdPsnuqPOZrcbbZmLDqYZTrFZIappz8k0Wgp0l1kMM6E/out.png", "started_at": "2024-10-20T19:31:14.761212Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xmnt06t0dsrgj0cjndkv7try1c", "cancel": "https://api.replicate.com/v1/predictions/xmnt06t0dsrgj0cjndkv7try1c/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 43882 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:31, 2.02it/s] 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21ID26fyrd7wxsrgj0cjndqvxbapagStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- An image of a Pikachu wearing a birthday hat and playing guitar.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "An image of a Pikachu wearing a birthday hat and playing guitar.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "An image of a Pikachu wearing a birthday hat and playing guitar.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "An image of a Pikachu wearing a birthday hat and playing guitar.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "An image of a Pikachu wearing a birthday hat and playing guitar.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:38:33.446603Z", "created_at": "2024-10-20T19:38:16.174000Z", "data_removed": false, "error": null, "id": "26fyrd7wxsrgj0cjndqvxbapag", "input": { "prompt": "An image of a Pikachu wearing a birthday hat and playing guitar.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 58920\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.35it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.33it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.32it/s]\n 6%|▋ | 4/64 [00:00<00:13, 4.32it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.31it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.31it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.31it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.31it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.30it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.30it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.30it/s]\n 19%|█▉ | 12/64 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4.32it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.32it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.32it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.32it/s]\n 94%|█████████▍| 60/64 [00:13<00:00, 4.32it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.32it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.31it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.31it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.32it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.31it/s]", "metrics": { "predict_time": 17.166660443, "total_time": 17.272603 }, "output": "https://replicate.delivery/pbxt/mdgA3Nvx9bJIEVTWQDqJzBzrueShyFIK3xymmc7Dvf444woTA/out.png", "started_at": "2024-10-20T19:38:16.279943Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/26fyrd7wxsrgj0cjndqvxbapag", "cancel": "https://api.replicate.com/v1/predictions/26fyrd7wxsrgj0cjndqvxbapag/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 58920 0%| | 0/64 [00:00<?, ?it/s] 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDcvx6jzbsgdrgj0cjndrasph8n8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A statue of a lion stands in front of a building.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A statue of a lion stands in front of a building.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A statue of a lion stands in front of a building.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A statue of a lion stands in front of a building.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A statue of a lion stands in front of a building.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:39:05.346581Z", "created_at": "2024-10-20T19:38:48.067000Z", "data_removed": false, "error": null, "id": "cvx6jzbsgdrgj0cjndrasph8n8", "input": { "prompt": "A statue of a lion stands in front of a building.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 2720\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.34it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.33it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.33it/s]\n 6%|▋ | 4/64 [00:00<00:13, 4.32it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.30it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.31it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.32it/s]\n 12%|█▎ | 8/64 [00:01<00:12, 4.32it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.33it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.33it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.33it/s]\n 19%|█▉ | 12/64 [00:02<00:12, 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89%|████████▉ | 57/64 [00:13<00:01, 4.30it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.30it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.30it/s]\n 94%|█████████▍| 60/64 [00:13<00:00, 4.30it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.30it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.30it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.30it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.30it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.31it/s]", "metrics": { "predict_time": 17.174765848, "total_time": 17.279581 }, "output": "https://replicate.delivery/pbxt/PBFrPKt1JSoEOxBTSH5dTmlYG0VRLtOx5vfSfZjPqE5X5woTA/out.png", "started_at": "2024-10-20T19:38:48.171815Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/cvx6jzbsgdrgj0cjndrasph8n8", "cancel": "https://api.replicate.com/v1/predictions/cvx6jzbsgdrgj0cjndrasph8n8/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 2720 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 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78%|███████▊ | 50/64 [00:11<00:03, 4.30it/s] 80%|███████▉ | 51/64 [00:11<00:03, 4.30it/s] 81%|████████▏ | 52/64 [00:12<00:02, 4.30it/s] 83%|████████▎ | 53/64 [00:12<00:02, 4.30it/s] 84%|████████▍ | 54/64 [00:12<00:02, 4.31it/s] 86%|████████▌ | 55/64 [00:12<00:02, 4.30it/s] 88%|████████▊ | 56/64 [00:12<00:01, 4.30it/s] 89%|████████▉ | 57/64 [00:13<00:01, 4.30it/s] 91%|█████████ | 58/64 [00:13<00:01, 4.30it/s] 92%|█████████▏| 59/64 [00:13<00:01, 4.30it/s] 94%|█████████▍| 60/64 [00:13<00:00, 4.30it/s] 95%|█████████▌| 61/64 [00:14<00:00, 4.30it/s] 97%|█████████▋| 62/64 [00:14<00:00, 4.30it/s] 98%|█████████▊| 63/64 [00:14<00:00, 4.30it/s] 100%|██████████| 64/64 [00:14<00:00, 4.30it/s] 100%|██████████| 64/64 [00:14<00:00, 4.31it/s]Prediction
chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21ID66djp0r575rgp0cjndrrtra49rStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A white and blue coffee mug with a picture of a man on it
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A white and blue coffee mug with a picture of a man on it", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A white and blue coffee mug with a picture of a man on it", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A white and blue coffee mug with a picture of a man on it", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A white and blue coffee mug with a picture of a man on it", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:39:41.060296Z", "created_at": "2024-10-20T19:39:23.833000Z", "data_removed": false, "error": null, "id": "66djp0r575rgp0cjndrrtra49r", "input": { "prompt": "A white and blue coffee mug with a picture of a man on it", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 32926\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.29it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.30it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.30it/s]\n 6%|▋ | 4/64 [00:00<00:13, 4.32it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.32it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.33it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.33it/s]\n 12%|█▎ | 8/64 [00:01<00:12, 4.33it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.32it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.33it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.32it/s]\n 19%|█▉ | 12/64 [00:02<00:12, 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4.30it/s]\n 56%|█████▋ | 36/64 [00:08<00:06, 4.30it/s]\n 58%|█████▊ | 37/64 [00:08<00:06, 4.30it/s]\n 59%|█████▉ | 38/64 [00:08<00:06, 4.30it/s]\n 61%|██████ | 39/64 [00:09<00:05, 4.30it/s]\n 62%|██████▎ | 40/64 [00:09<00:05, 4.30it/s]\n 64%|██████▍ | 41/64 [00:09<00:05, 4.30it/s]\n 66%|██████▌ | 42/64 [00:09<00:05, 4.30it/s]\n 67%|██████▋ | 43/64 [00:09<00:04, 4.29it/s]\n 69%|██████▉ | 44/64 [00:10<00:04, 4.30it/s]\n 70%|███████ | 45/64 [00:10<00:04, 4.30it/s]\n 72%|███████▏ | 46/64 [00:10<00:04, 4.29it/s]\n 73%|███████▎ | 47/64 [00:10<00:03, 4.29it/s]\n 75%|███████▌ | 48/64 [00:11<00:03, 4.29it/s]\n 77%|███████▋ | 49/64 [00:11<00:03, 4.21it/s]\n 78%|███████▊ | 50/64 [00:11<00:03, 4.24it/s]\n 80%|███████▉ | 51/64 [00:11<00:03, 4.25it/s]\n 81%|████████▏ | 52/64 [00:12<00:02, 4.27it/s]\n 83%|████████▎ | 53/64 [00:12<00:02, 4.27it/s]\n 84%|████████▍ | 54/64 [00:12<00:02, 4.28it/s]\n 86%|████████▌ | 55/64 [00:12<00:02, 4.29it/s]\n 88%|████████▊ | 56/64 [00:13<00:01, 4.29it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.29it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.29it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.29it/s]\n 94%|█████████▍| 60/64 [00:13<00:00, 4.29it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.29it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.29it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.29it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.30it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.30it/s]", "metrics": { "predict_time": 17.122894572, "total_time": 17.227296 }, "output": "https://replicate.delivery/pbxt/DOm1HUpARh68JFBEonRAtuqfkqDWPwQzsHyZFLfs49975woTA/out.png", "started_at": "2024-10-20T19:39:23.937401Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/66djp0r575rgp0cjndrrtra49r", "cancel": "https://api.replicate.com/v1/predictions/66djp0r575rgp0cjndrrtra49r/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 32926 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 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78%|███████▊ | 50/64 [00:11<00:03, 4.24it/s] 80%|███████▉ | 51/64 [00:11<00:03, 4.25it/s] 81%|████████▏ | 52/64 [00:12<00:02, 4.27it/s] 83%|████████▎ | 53/64 [00:12<00:02, 4.27it/s] 84%|████████▍ | 54/64 [00:12<00:02, 4.28it/s] 86%|████████▌ | 55/64 [00:12<00:02, 4.29it/s] 88%|████████▊ | 56/64 [00:13<00:01, 4.29it/s] 89%|████████▉ | 57/64 [00:13<00:01, 4.29it/s] 91%|█████████ | 58/64 [00:13<00:01, 4.29it/s] 92%|█████████▏| 59/64 [00:13<00:01, 4.29it/s] 94%|█████████▍| 60/64 [00:13<00:00, 4.29it/s] 95%|█████████▌| 61/64 [00:14<00:00, 4.29it/s] 97%|█████████▋| 62/64 [00:14<00:00, 4.29it/s] 98%|█████████▊| 63/64 [00:14<00:00, 4.29it/s] 100%|██████████| 64/64 [00:14<00:00, 4.30it/s] 100%|██████████| 64/64 [00:14<00:00, 4.30it/s]Prediction
chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDnz8869wt6hrgj0cjndrvq21v5rStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A bronze statue of an owl with its wings spread.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A bronze statue of an owl with its wings spread.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A bronze statue of an owl with its wings spread.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A bronze statue of an owl with its wings spread.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A bronze statue of an owl with its wings spread.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:40:19.234347Z", "created_at": "2024-10-20T19:40:01.972000Z", "data_removed": false, "error": null, "id": "nz8869wt6hrgj0cjndrvq21v5r", "input": { "prompt": "A bronze statue of an owl with its wings spread.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 48735\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.36it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.34it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.32it/s]\n 6%|▋ | 4/64 [00:00<00:13, 4.32it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.31it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.30it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.30it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.31it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.30it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.30it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.30it/s]\n 19%|█▉ | 12/64 [00:02<00:12, 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89%|████████▉ | 57/64 [00:13<00:01, 4.29it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.26it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.27it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.27it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.28it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.28it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.28it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.29it/s]\n100%|██████████| 64/64 [00:14<00:00, 4.28it/s]", "metrics": { "predict_time": 17.157780067, "total_time": 17.262347 }, "output": "https://replicate.delivery/pbxt/p8TdfeUWezXHfTe2708N65Sze6z27geMaXew2OPY03sOh6woTA/out.png", "started_at": "2024-10-20T19:40:02.076567Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nz8869wt6hrgj0cjndrvq21v5r", "cancel": "https://api.replicate.com/v1/predictions/nz8869wt6hrgj0cjndrvq21v5r/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 48735 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21ID3w7ny78fd9rgm0cjndsbchdbs8StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A white table with a vase of flowers and a cup of coffee on top of it.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A white table with a vase of flowers and a cup of coffee on top of it.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A white table with a vase of flowers and a cup of coffee on top of it.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A white table with a vase of flowers and a cup of coffee on top of it.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A white table with a vase of flowers and a cup of coffee on top of it.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:40:54.089299Z", "created_at": "2024-10-20T19:40:31.978000Z", "data_removed": false, "error": null, "id": "3w7ny78fd9rgm0cjndsbchdbs8", "input": { "prompt": "A white table with a vase of flowers and a cup of coffee on top of it.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 24110\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.32it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.30it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.29it/s]\n 6%|▋ | 4/64 [00:00<00:13, 4.29it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.29it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.29it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.29it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.28it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.29it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.29it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.25it/s]\n 19%|█▉ | 12/64 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[00:08<00:06, 4.28it/s]\n 56%|█████▋ | 36/64 [00:08<00:06, 4.19it/s]\n 58%|█████▊ | 37/64 [00:08<00:06, 4.21it/s]\n 59%|█████▉ | 38/64 [00:08<00:06, 4.23it/s]\n 61%|██████ | 39/64 [00:09<00:05, 4.25it/s]\n 62%|██████▎ | 40/64 [00:09<00:05, 4.26it/s]\n 64%|██████▍ | 41/64 [00:09<00:05, 4.26it/s]\n 66%|██████▌ | 42/64 [00:09<00:05, 4.26it/s]\n 67%|██████▋ | 43/64 [00:10<00:04, 4.26it/s]\n 69%|██████▉ | 44/64 [00:10<00:04, 4.26it/s]\n 70%|███████ | 45/64 [00:10<00:04, 4.27it/s]\n 72%|███████▏ | 46/64 [00:10<00:04, 4.27it/s]\n 73%|███████▎ | 47/64 [00:11<00:03, 4.27it/s]\n 75%|███████▌ | 48/64 [00:11<00:03, 4.27it/s]\n 77%|███████▋ | 49/64 [00:11<00:03, 4.27it/s]\n 78%|███████▊ | 50/64 [00:11<00:03, 4.27it/s]\n 80%|███████▉ | 51/64 [00:11<00:03, 4.27it/s]\n 81%|████████▏ | 52/64 [00:12<00:02, 4.27it/s]\n 83%|████████▎ | 53/64 [00:12<00:02, 4.27it/s]\n 84%|████████▍ | 54/64 [00:12<00:02, 4.27it/s]\n 86%|████████▌ | 55/64 [00:12<00:02, 4.27it/s]\n 88%|████████▊ | 56/64 [00:13<00:01, 4.27it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.24it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.25it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.26it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.26it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.27it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.27it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.24it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.25it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.26it/s]", "metrics": { "predict_time": 17.262786664, "total_time": 22.111299 }, "output": "https://replicate.delivery/pbxt/VIXg91UwRGY0EhdCGPbkxbNWClHVlS1c52Odf904If6E7woTA/out.png", "started_at": "2024-10-20T19:40:36.826512Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3w7ny78fd9rgm0cjndsbchdbs8", "cancel": "https://api.replicate.com/v1/predictions/3w7ny78fd9rgm0cjndsbchdbs8/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 24110 0%| | 0/64 [00:00<?, ?it/s] 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDk4hc9esrcxrgg0cjndt8ky68hrStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A metal sculpture of a deer with antlers
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A metal sculpture of a deer with antlers", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A metal sculpture of a deer with antlers", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A metal sculpture of a deer with antlers", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A metal sculpture of a deer with antlers", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:43:18.710164Z", "created_at": "2024-10-20T19:42:53.543000Z", "data_removed": false, "error": null, "id": "k4hc9esrcxrgg0cjndt8ky68hr", "input": { "prompt": "A metal sculpture of a deer with antlers", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 11800\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.29it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.26it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.26it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.25it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.25it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.24it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.24it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.24it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.24it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.23it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.23it/s]\n 19%|█▉ | 12/64 [00:02<00:12, 4.23it/s]\n 20%|██ 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36/64 [00:08<00:06, 4.23it/s]\n 58%|█████▊ | 37/64 [00:08<00:06, 4.22it/s]\n 59%|█████▉ | 38/64 [00:08<00:06, 4.22it/s]\n 61%|██████ | 39/64 [00:09<00:05, 4.21it/s]\n 62%|██████▎ | 40/64 [00:09<00:05, 4.21it/s]\n 64%|██████▍ | 41/64 [00:09<00:05, 4.21it/s]\n 66%|██████▌ | 42/64 [00:09<00:05, 4.22it/s]\n 67%|██████▋ | 43/64 [00:10<00:04, 4.22it/s]\n 69%|██████▉ | 44/64 [00:10<00:04, 4.22it/s]\n 70%|███████ | 45/64 [00:10<00:04, 4.22it/s]\n 72%|███████▏ | 46/64 [00:10<00:04, 4.22it/s]\n 73%|███████▎ | 47/64 [00:11<00:04, 4.22it/s]\n 75%|███████▌ | 48/64 [00:11<00:03, 4.22it/s]\n 77%|███████▋ | 49/64 [00:11<00:03, 4.22it/s]\n 78%|███████▊ | 50/64 [00:11<00:03, 4.22it/s]\n 80%|███████▉ | 51/64 [00:12<00:03, 4.22it/s]\n 81%|████████▏ | 52/64 [00:12<00:02, 4.22it/s]\n 83%|████████▎ | 53/64 [00:12<00:02, 4.22it/s]\n 84%|████████▍ | 54/64 [00:12<00:02, 4.22it/s]\n 86%|████████▌ | 55/64 [00:13<00:02, 4.22it/s]\n 88%|████████▊ | 56/64 [00:13<00:01, 4.16it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.18it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.19it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.20it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.20it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.21it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.21it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.21it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.22it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.22it/s]", "metrics": { "predict_time": 17.350950839, "total_time": 25.167164 }, "output": "https://replicate.delivery/pbxt/PD67xtmfv3Qrd6aCVVr4I4HIeiHeomRJ92D67p3y361q6hRnA/out.png", "started_at": "2024-10-20T19:43:01.359213Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/k4hc9esrcxrgg0cjndt8ky68hr", "cancel": "https://api.replicate.com/v1/predictions/k4hc9esrcxrgg0cjndt8ky68hr/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 11800 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:14, 4.29it/s] 3%|▎ | 2/64 [00:00<00:14, 4.26it/s] 5%|▍ | 3/64 [00:00<00:14, 4.26it/s] 6%|▋ | 4/64 [00:00<00:14, 4.25it/s] 8%|▊ | 5/64 [00:01<00:13, 4.25it/s] 9%|▉ | 6/64 [00:01<00:13, 4.24it/s] 11%|█ | 7/64 [00:01<00:13, 4.24it/s] 12%|█▎ | 8/64 [00:01<00:13, 4.24it/s] 14%|█▍ | 9/64 [00:02<00:12, 4.24it/s] 16%|█▌ | 10/64 [00:02<00:12, 4.23it/s] 17%|█▋ | 11/64 [00:02<00:12, 4.23it/s] 19%|█▉ | 12/64 [00:02<00:12, 4.23it/s] 20%|██ | 13/64 [00:03<00:12, 4.23it/s] 22%|██▏ | 14/64 [00:03<00:11, 4.23it/s] 23%|██▎ | 15/64 [00:03<00:11, 4.23it/s] 25%|██▌ | 16/64 [00:03<00:11, 4.23it/s] 27%|██▋ | 17/64 [00:04<00:11, 4.22it/s] 28%|██▊ | 18/64 [00:04<00:10, 4.22it/s] 30%|██▉ | 19/64 [00:04<00:10, 4.22it/s] 31%|███▏ | 20/64 [00:04<00:10, 4.23it/s] 33%|███▎ | 21/64 [00:04<00:10, 4.23it/s] 34%|███▍ | 22/64 [00:05<00:09, 4.23it/s] 36%|███▌ | 23/64 [00:05<00:09, 4.23it/s] 38%|███▊ | 24/64 [00:05<00:09, 4.22it/s] 39%|███▉ | 25/64 [00:05<00:09, 4.22it/s] 41%|████ | 26/64 [00:06<00:08, 4.22it/s] 42%|████▏ | 27/64 [00:06<00:08, 4.22it/s] 44%|████▍ | 28/64 [00:06<00:08, 4.22it/s] 45%|████▌ | 29/64 [00:06<00:08, 4.22it/s] 47%|████▋ | 30/64 [00:07<00:08, 4.22it/s] 48%|████▊ | 31/64 [00:07<00:07, 4.22it/s] 50%|█████ | 32/64 [00:07<00:07, 4.22it/s] 52%|█████▏ | 33/64 [00:07<00:07, 4.22it/s] 53%|█████▎ | 34/64 [00:08<00:07, 4.22it/s] 55%|█████▍ | 35/64 [00:08<00:06, 4.23it/s] 56%|█████▋ | 36/64 [00:08<00:06, 4.23it/s] 58%|█████▊ | 37/64 [00:08<00:06, 4.22it/s] 59%|█████▉ | 38/64 [00:08<00:06, 4.22it/s] 61%|██████ | 39/64 [00:09<00:05, 4.21it/s] 62%|██████▎ | 40/64 [00:09<00:05, 4.21it/s] 64%|██████▍ | 41/64 [00:09<00:05, 4.21it/s] 66%|██████▌ | 42/64 [00:09<00:05, 4.22it/s] 67%|██████▋ | 43/64 [00:10<00:04, 4.22it/s] 69%|██████▉ | 44/64 [00:10<00:04, 4.22it/s] 70%|███████ | 45/64 [00:10<00:04, 4.22it/s] 72%|███████▏ | 46/64 [00:10<00:04, 4.22it/s] 73%|███████▎ | 47/64 [00:11<00:04, 4.22it/s] 75%|███████▌ | 48/64 [00:11<00:03, 4.22it/s] 77%|███████▋ | 49/64 [00:11<00:03, 4.22it/s] 78%|███████▊ | 50/64 [00:11<00:03, 4.22it/s] 80%|███████▉ | 51/64 [00:12<00:03, 4.22it/s] 81%|████████▏ | 52/64 [00:12<00:02, 4.22it/s] 83%|████████▎ | 53/64 [00:12<00:02, 4.22it/s] 84%|████████▍ | 54/64 [00:12<00:02, 4.22it/s] 86%|████████▌ | 55/64 [00:13<00:02, 4.22it/s] 88%|████████▊ | 56/64 [00:13<00:01, 4.16it/s] 89%|████████▉ | 57/64 [00:13<00:01, 4.18it/s] 91%|█████████ | 58/64 [00:13<00:01, 4.19it/s] 92%|█████████▏| 59/64 [00:13<00:01, 4.20it/s] 94%|█████████▍| 60/64 [00:14<00:00, 4.20it/s] 95%|█████████▌| 61/64 [00:14<00:00, 4.21it/s] 97%|█████████▋| 62/64 [00:14<00:00, 4.21it/s] 98%|█████████▊| 63/64 [00:14<00:00, 4.21it/s] 100%|██████████| 64/64 [00:15<00:00, 4.22it/s] 100%|██████████| 64/64 [00:15<00:00, 4.22it/s]Prediction
chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21ID3caj5jbde5rgp0cjndt8nbaw2wStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A lion's head is shown in a grayscale image
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A lion's head is shown in a grayscale image", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A lion's head is shown in a grayscale image", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A lion's head is shown in a grayscale image", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A lion\'s head is shown in a grayscale image", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:43:36.238440Z", "created_at": "2024-10-20T19:43:07.121000Z", "data_removed": false, "error": null, "id": "3caj5jbde5rgp0cjndt8nbaw2w", "input": { "prompt": "A lion's head is shown in a grayscale image", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 5345\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.28it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.25it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.24it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.23it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.23it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.23it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.23it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.23it/s]\n 14%|█▍ | 9/64 [00:02<00:13, 4.23it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.22it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.22it/s]\n 19%|█▉ | 12/64 [00:02<00:12, 4.22it/s]\n 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[00:13<00:01, 4.21it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.21it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.20it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.21it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.21it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.21it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.21it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.22it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.22it/s]", "metrics": { "predict_time": 17.317003426, "total_time": 29.11744 }, "output": "https://replicate.delivery/pbxt/a4El4KZhXo5uJB5Pe0zfaffhLTThtaOwncfGAyEfyzkoZPM6E/out.png", "started_at": "2024-10-20T19:43:18.921436Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/3caj5jbde5rgp0cjndt8nbaw2w", "cancel": "https://api.replicate.com/v1/predictions/3caj5jbde5rgp0cjndt8nbaw2w/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 5345 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:14, 4.28it/s] 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[00:11<00:03, 4.22it/s] 80%|███████▉ | 51/64 [00:12<00:03, 4.22it/s] 81%|████████▏ | 52/64 [00:12<00:02, 4.21it/s] 83%|████████▎ | 53/64 [00:12<00:02, 4.21it/s] 84%|████████▍ | 54/64 [00:12<00:02, 4.21it/s] 86%|████████▌ | 55/64 [00:13<00:02, 4.21it/s] 88%|████████▊ | 56/64 [00:13<00:01, 4.21it/s] 89%|████████▉ | 57/64 [00:13<00:01, 4.21it/s] 91%|█████████ | 58/64 [00:13<00:01, 4.21it/s] 92%|█████████▏| 59/64 [00:13<00:01, 4.20it/s] 94%|█████████▍| 60/64 [00:14<00:00, 4.21it/s] 95%|█████████▌| 61/64 [00:14<00:00, 4.21it/s] 97%|█████████▋| 62/64 [00:14<00:00, 4.21it/s] 98%|█████████▊| 63/64 [00:14<00:00, 4.21it/s] 100%|██████████| 64/64 [00:15<00:00, 4.22it/s] 100%|██████████| 64/64 [00:15<00:00, 4.22it/s]Prediction
chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21ID4zk9sayqp5rgj0cjndtazmmy6wStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A sculpture of a Greek woman head with a headband and a head of hair
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A sculpture of a Greek woman head with a headband and a head of hair", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A sculpture of a Greek woman head with a headband and a head of hair", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A sculpture of a Greek woman head with a headband and a head of hair", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A sculpture of a Greek woman head with a headband and a head of hair", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:43:53.602855Z", "created_at": "2024-10-20T19:43:34.321000Z", "data_removed": false, "error": null, "id": "4zk9sayqp5rgj0cjndtazmmy6w", "input": { "prompt": "A sculpture of a Greek woman head with a headband and a head of hair", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 13783\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.28it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.25it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.24it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.24it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.23it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.23it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.22it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.22it/s]\n 14%|█▍ | 9/64 [00:02<00:13, 4.21it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.21it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.21it/s]\n 19%|█▉ | 12/64 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDmh0fc2gvfnrgp0cjndvvyakff0StatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- Spiderman as Wolverine with detailed muscular features and a full face, trending on multiple art platforms, created with hyperdetailed Unreal Engine, and optimized for high resolution viewing.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "Spiderman as Wolverine with detailed muscular features and a full face, trending on multiple art platforms, created with hyperdetailed Unreal Engine, and optimized for high resolution viewing.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "Spiderman as Wolverine with detailed muscular features and a full face, trending on multiple art platforms, created with hyperdetailed Unreal Engine, and optimized for high resolution viewing.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "Spiderman as Wolverine with detailed muscular features and a full face, trending on multiple art platforms, created with hyperdetailed Unreal Engine, and optimized for high resolution viewing.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "Spiderman as Wolverine with detailed muscular features and a full face, trending on multiple art platforms, created with hyperdetailed Unreal Engine, and optimized for high resolution viewing.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:46:20.220823Z", "created_at": "2024-10-20T19:46:02.749000Z", "data_removed": false, "error": null, "id": "mh0fc2gvfnrgp0cjndvvyakff0", "input": { "prompt": "Spiderman as Wolverine with detailed muscular features and a full face, trending on multiple art platforms, created with hyperdetailed Unreal Engine, and optimized for high resolution viewing.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 25955\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.31it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.28it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.27it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.26it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.25it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.25it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.25it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.26it/s]\n 14%|█▍ | 9/64 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4.24it/s]\n 52%|█████▏ | 33/64 [00:07<00:07, 4.24it/s]\n 53%|█████▎ | 34/64 [00:08<00:07, 4.24it/s]\n 55%|█████▍ | 35/64 [00:08<00:06, 4.23it/s]\n 56%|█████▋ | 36/64 [00:08<00:06, 4.24it/s]\n 58%|█████▊ | 37/64 [00:08<00:06, 4.24it/s]\n 59%|█████▉ | 38/64 [00:08<00:06, 4.24it/s]\n 61%|██████ | 39/64 [00:09<00:05, 4.23it/s]\n 62%|██████▎ | 40/64 [00:09<00:05, 4.19it/s]\n 64%|██████▍ | 41/64 [00:09<00:05, 4.20it/s]\n 66%|██████▌ | 42/64 [00:09<00:05, 4.21it/s]\n 67%|██████▋ | 43/64 [00:10<00:04, 4.21it/s]\n 69%|██████▉ | 44/64 [00:10<00:04, 4.22it/s]\n 70%|███████ | 45/64 [00:10<00:04, 4.22it/s]\n 72%|███████▏ | 46/64 [00:10<00:04, 4.22it/s]\n 73%|███████▎ | 47/64 [00:11<00:04, 4.22it/s]\n 75%|███████▌ | 48/64 [00:11<00:03, 4.22it/s]\n 77%|███████▋ | 49/64 [00:11<00:03, 4.22it/s]\n 78%|███████▊ | 50/64 [00:11<00:03, 4.22it/s]\n 80%|███████▉ | 51/64 [00:12<00:03, 4.22it/s]\n 81%|████████▏ | 52/64 [00:12<00:02, 4.22it/s]\n 83%|████████▎ | 53/64 [00:12<00:02, 4.23it/s]\n 84%|████████▍ | 54/64 [00:12<00:02, 4.23it/s]\n 86%|████████▌ | 55/64 [00:12<00:02, 4.23it/s]\n 88%|████████▊ | 56/64 [00:13<00:01, 4.22it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.22it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.22it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.23it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.23it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.24it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.25it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.25it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.26it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.24it/s]", "metrics": { "predict_time": 17.376977491, "total_time": 17.471823 }, "output": "https://replicate.delivery/pbxt/KZXIcZZmQsrWEVKvpYyTTtESh8Cffs1If8onwBeg6fgSBIGdC/out.png", "started_at": "2024-10-20T19:46:02.843845Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mh0fc2gvfnrgp0cjndvvyakff0", "cancel": "https://api.replicate.com/v1/predictions/mh0fc2gvfnrgp0cjndvvyakff0/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 25955 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:14, 4.31it/s] 3%|▎ | 2/64 [00:00<00:14, 4.28it/s] 5%|▍ | 3/64 [00:00<00:14, 4.27it/s] 6%|▋ | 4/64 [00:00<00:14, 4.26it/s] 8%|▊ | 5/64 [00:01<00:13, 4.25it/s] 9%|▉ | 6/64 [00:01<00:13, 4.25it/s] 11%|█ | 7/64 [00:01<00:13, 4.25it/s] 12%|█▎ | 8/64 [00:01<00:13, 4.26it/s] 14%|█▍ | 9/64 [00:02<00:12, 4.26it/s] 16%|█▌ | 10/64 [00:02<00:12, 4.25it/s] 17%|█▋ | 11/64 [00:02<00:12, 4.25it/s] 19%|█▉ | 12/64 [00:02<00:12, 4.25it/s] 20%|██ | 13/64 [00:03<00:11, 4.26it/s] 22%|██▏ | 14/64 [00:03<00:11, 4.26it/s] 23%|██▎ | 15/64 [00:03<00:11, 4.25it/s] 25%|██▌ | 16/64 [00:03<00:11, 4.26it/s] 27%|██▋ | 17/64 [00:03<00:11, 4.25it/s] 28%|██▊ | 18/64 [00:04<00:10, 4.25it/s] 30%|██▉ | 19/64 [00:04<00:10, 4.24it/s] 31%|███▏ | 20/64 [00:04<00:10, 4.24it/s] 33%|███▎ | 21/64 [00:04<00:10, 4.24it/s] 34%|███▍ | 22/64 [00:05<00:09, 4.24it/s] 36%|███▌ | 23/64 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4.22it/s] 73%|███████▎ | 47/64 [00:11<00:04, 4.22it/s] 75%|███████▌ | 48/64 [00:11<00:03, 4.22it/s] 77%|███████▋ | 49/64 [00:11<00:03, 4.22it/s] 78%|███████▊ | 50/64 [00:11<00:03, 4.22it/s] 80%|███████▉ | 51/64 [00:12<00:03, 4.22it/s] 81%|████████▏ | 52/64 [00:12<00:02, 4.22it/s] 83%|████████▎ | 53/64 [00:12<00:02, 4.23it/s] 84%|████████▍ | 54/64 [00:12<00:02, 4.23it/s] 86%|████████▌ | 55/64 [00:12<00:02, 4.23it/s] 88%|████████▊ | 56/64 [00:13<00:01, 4.22it/s] 89%|████████▉ | 57/64 [00:13<00:01, 4.22it/s] 91%|█████████ | 58/64 [00:13<00:01, 4.22it/s] 92%|█████████▏| 59/64 [00:13<00:01, 4.23it/s] 94%|█████████▍| 60/64 [00:14<00:00, 4.23it/s] 95%|█████████▌| 61/64 [00:14<00:00, 4.24it/s] 97%|█████████▋| 62/64 [00:14<00:00, 4.25it/s] 98%|█████████▊| 63/64 [00:14<00:00, 4.25it/s] 100%|██████████| 64/64 [00:15<00:00, 4.26it/s] 100%|██████████| 64/64 [00:15<00:00, 4.24it/s]Prediction
chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDfnzx4cae1hrgp0cjndvtk824cgStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A digital painting of a Pokémon named Faerow in a concept art style.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A digital painting of a Pokémon named Faerow in a concept art style.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A digital painting of a Pokémon named Faerow in a concept art style.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A digital painting of a Pokémon named Faerow in a concept art style.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A digital painting of a Pokémon named Faerow in a concept art style.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:46:37.585521Z", "created_at": "2024-10-20T19:46:15.692000Z", "data_removed": false, "error": null, "id": "fnzx4cae1hrgp0cjndvtk824cg", "input": { "prompt": "A digital painting of a Pokémon named Faerow in a concept art style.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 38888\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.27it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.20it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.21it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.22it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.22it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.22it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.24it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.19it/s]\n 14%|█▍ | 9/64 [00:02<00:13, 4.21it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.23it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.23it/s]\n 19%|█▉ | 12/64 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4.25it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.25it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.25it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.25it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.25it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.24it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.24it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.24it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.25it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.24it/s]", "metrics": { "predict_time": 17.163241429, "total_time": 21.893521 }, "output": "https://replicate.delivery/pbxt/HlGnrvIwDm7RJFjkIPJQfxnZEA4JmefqbKnsziyC5fvyBEjOB/out.png", "started_at": "2024-10-20T19:46:20.422280Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fnzx4cae1hrgp0cjndvtk824cg", "cancel": "https://api.replicate.com/v1/predictions/fnzx4cae1hrgp0cjndvtk824cg/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 38888 0%| | 0/64 [00:00<?, ?it/s] 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21ID2677bb8039rgj0cjndwvn5fcscStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- A samurai in space.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "A samurai in space.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "A samurai in space.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "A samurai in space.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "A samurai in space.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:48:38.493858Z", "created_at": "2024-10-20T19:48:06.810000Z", "data_removed": false, "error": null, "id": "2677bb8039rgj0cjndwvn5fcsc", "input": { "prompt": "A samurai in space.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 40671\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.29it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.27it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.25it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.24it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.24it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.23it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.24it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.23it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.23it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.23it/s]\n 17%|█▋ | 11/64 [00:02<00:12, 4.23it/s]\n 19%|█▉ | 12/64 [00:02<00:12, 4.23it/s]\n 20%|██ | 13/64 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4.22it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.22it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.22it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.22it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.22it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.22it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.21it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.22it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.22it/s]", "metrics": { "predict_time": 17.286325492, "total_time": 31.683858 }, "output": "https://replicate.delivery/pbxt/k7BFxkykvkKxGxnqPvgCnFtf1KIOrXsteTlaHqSVH0cVCxoTA/out.png", "started_at": "2024-10-20T19:48:21.207532Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/2677bb8039rgj0cjndwvn5fcsc", "cancel": "https://api.replicate.com/v1/predictions/2677bb8039rgj0cjndwvn5fcsc/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing seed: 40671 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:14, 4.29it/s] 3%|▎ | 2/64 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chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21IDmmkjjxy96hrgm0cjndw9a3z9tcStatusSucceededSourceWebHardwareA40Total durationCreatedInput
- prompt
- The image features Breton monks resembling Rasputin from The Lorax, with cinematic lighting and a shallow depth of field.
- guidance_scale
- 9
- negative_prompt
- worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark
- num_inference_steps
- 64
{ "prompt": "The image features Breton monks resembling Rasputin from The Lorax, with cinematic lighting and a shallow depth of field.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", { input: { prompt: "The image features Breton monks resembling Rasputin from The Lorax, with cinematic lighting and a shallow depth of field.", guidance_scale: 9, negative_prompt: "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", num_inference_steps: 64 } } ); // To access the file URL: console.log(output.url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output);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 chenxwh/meissonic using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", input={ "prompt": "The image features Breton monks resembling Rasputin from The Lorax, with cinematic lighting and a shallow depth of field.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run chenxwh/meissonic 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": "chenxwh/meissonic:92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21", "input": { "prompt": "The image features Breton monks resembling Rasputin from The Lorax, with cinematic lighting and a shallow depth of field.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-10-20T19:48:21.006152Z", "created_at": "2024-10-20T19:47:52.756000Z", "data_removed": false, "error": null, "id": "mmkjjxy96hrgm0cjndw9a3z9tc", "input": { "prompt": "The image features Breton monks resembling Rasputin from The Lorax, with cinematic lighting and a shallow depth of field.", "guidance_scale": 9, "negative_prompt": "worst quality, low quality, low res, blurry, distortion, watermark, logo, signature, text, jpeg artifacts, signature, sketch, duplicate, ugly, identifying mark", "num_inference_steps": 64 }, "logs": "Using seed: 22733\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:14, 4.29it/s]\n 3%|▎ | 2/64 [00:00<00:14, 4.27it/s]\n 5%|▍ | 3/64 [00:00<00:14, 4.26it/s]\n 6%|▋ | 4/64 [00:00<00:14, 4.25it/s]\n 8%|▊ | 5/64 [00:01<00:13, 4.25it/s]\n 9%|▉ | 6/64 [00:01<00:13, 4.26it/s]\n 11%|█ | 7/64 [00:01<00:13, 4.26it/s]\n 12%|█▎ | 8/64 [00:01<00:13, 4.25it/s]\n 14%|█▍ | 9/64 [00:02<00:12, 4.25it/s]\n 16%|█▌ | 10/64 [00:02<00:12, 4.25it/s]\n 17%|█▋ 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[00:08<00:07, 4.22it/s]\n 55%|█████▍ | 35/64 [00:08<00:06, 4.22it/s]\n 56%|█████▋ | 36/64 [00:08<00:06, 4.23it/s]\n 58%|█████▊ | 37/64 [00:08<00:06, 4.23it/s]\n 59%|█████▉ | 38/64 [00:08<00:06, 4.23it/s]\n 61%|██████ | 39/64 [00:09<00:05, 4.22it/s]\n 62%|██████▎ | 40/64 [00:09<00:05, 4.22it/s]\n 64%|██████▍ | 41/64 [00:09<00:05, 4.22it/s]\n 66%|██████▌ | 42/64 [00:09<00:05, 4.23it/s]\n 67%|██████▋ | 43/64 [00:10<00:04, 4.23it/s]\n 69%|██████▉ | 44/64 [00:10<00:04, 4.23it/s]\n 70%|███████ | 45/64 [00:10<00:04, 4.20it/s]\n 72%|███████▏ | 46/64 [00:10<00:04, 4.21it/s]\n 73%|███████▎ | 47/64 [00:11<00:04, 4.21it/s]\n 75%|███████▌ | 48/64 [00:11<00:03, 4.22it/s]\n 77%|███████▋ | 49/64 [00:11<00:03, 4.19it/s]\n 78%|███████▊ | 50/64 [00:11<00:03, 4.20it/s]\n 80%|███████▉ | 51/64 [00:12<00:03, 4.20it/s]\n 81%|████████▏ | 52/64 [00:12<00:02, 4.21it/s]\n 83%|████████▎ | 53/64 [00:12<00:02, 4.22it/s]\n 84%|████████▍ | 54/64 [00:12<00:02, 4.22it/s]\n 86%|████████▌ | 55/64 [00:13<00:02, 4.22it/s]\n 88%|████████▊ | 56/64 [00:13<00:01, 4.22it/s]\n 89%|████████▉ | 57/64 [00:13<00:01, 4.22it/s]\n 91%|█████████ | 58/64 [00:13<00:01, 4.22it/s]\n 92%|█████████▏| 59/64 [00:13<00:01, 4.23it/s]\n 94%|█████████▍| 60/64 [00:14<00:00, 4.22it/s]\n 95%|█████████▌| 61/64 [00:14<00:00, 4.23it/s]\n 97%|█████████▋| 62/64 [00:14<00:00, 4.23it/s]\n 98%|█████████▊| 63/64 [00:14<00:00, 4.22it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.23it/s]\n100%|██████████| 64/64 [00:15<00:00, 4.23it/s]", "metrics": { "predict_time": 17.375693794, "total_time": 28.250152 }, "output": "https://replicate.delivery/pbxt/b8hb5GyqyAafAyevgYQCk2tzw9O444dt60RiXepzI2ePIEjOB/out.png", "started_at": "2024-10-20T19:48:03.630458Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/mmkjjxy96hrgm0cjndw9a3z9tc", "cancel": "https://api.replicate.com/v1/predictions/mmkjjxy96hrgm0cjndw9a3z9tc/cancel" }, "version": "92c16966ef0dda80cf0afb11544371bfb2944025c47c4036615fcfd2f7515a21" }Generated inUsing 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