chenxwh/nova-t2i
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nova-t2i
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chenxwh/nova-t2i
Autoregressive Image Generation without Vector Quantization
chenxwh/video-retalking
Audio-based Lip Synchronization for Talking Head Video
chenxwh/openvoice
Updated to OpenVoice v2: Versatile Instant Voice Cloning
chenxwh/hunyuandit
A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
chenxwh/sdxl-flash
Fast sdxl with higher quality
chenxwh/omost
Convert LLM's coding to image generation
chenxwh/depth-anything-v2
Depth estimation with faster inference speed, fewer parameters, and higher depth accuracy.
chenxwh/diffsynth-exvideo
Extended video synthesis model that generates 128 frames
chenxwh/cogvlm2
CogVLM2: Visual Language Models for Image and Video Understanding
chenxwh/cogvlm2-video
CogVLM2: Visual Language Models for Image and Video Understanding
chenxwh/depthcrafter
Generating Consistent Long Depth Sequences for Open-world Videos
chenxwh/cogview3
Finer and Faster Text-to-Image Generation via Relay Diffusion
chenxwh/lotus
Diffusion-based Visual Foundation Model for High-quality Dense Prediction
chenxwh/ml-depth-pro
Sharp Monocular Metric Depth in Less Than a Second
chenxwh/hart
Efficient Visual Generation with Hybrid Autoregressive Transformer
chenxwh/meissonic
Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
chenxwh/depth-any-video
Depth Any Video with Scalable Synthetic Data
chenxwh/ltx-video
DiT-based video generation model for generating high-quality videos in real-time
chenxwh/ominicontrol-subject
Minimal and Universal Control for Diffusion Transformer - demo for Subject-driven generation
chenxwh/nitrofusion
High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training
chenxwh/nova-t2v
Autoregressive Video Generation without Vector Quantization
Prediction
chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3IDxn4r2sdce5rm80cm10491r5nt4StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- prompt
- a shiba inu wearing a beret and black turtleneck.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{ "prompt": "a shiba inu wearing a beret and black turtleneck.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", { input: { prompt: "a shiba inu wearing a beret and black turtleneck.", guidance_scale: 5, negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", num_diffusion_steps: 25, 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/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", input={ "prompt": "a shiba inu wearing a beret and black turtleneck.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run chenxwh/nova-t2i 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/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", "input": { "prompt": "a shiba inu wearing a beret and black turtleneck.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "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": "2024-12-27T12:14:08.344308Z", "created_at": "2024-12-27T12:12:53.745000Z", "data_removed": false, "error": null, "id": "xn4r2sdce5rm80cm10491r5nt4", "input": { "prompt": "a shiba inu wearing a beret and black turtleneck.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }, "logs": "Using seed: 20663\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:10, 5.97it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.05it/s]\n 5%|▍ | 3/64 [00:00<00:08, 7.43it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.52it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.64it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.71it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.73it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.80it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.77it/s]\n 16%|█▌ | 10/64 [00:01<00:06, 7.78it/s]\n 17%|█▋ | 11/64 [00:01<00:06, 7.79it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.80it/s]\n 20%|██ | 13/64 [00:01<00:06, 7.81it/s]\n 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58/64 [00:08<00:01, 5.54it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.49it/s]\n 94%|█████████▍| 60/64 [00:08<00:00, 5.34it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.26it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.22it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 5.15it/s]\n100%|██████████| 64/64 [00:09<00:00, 5.03it/s]\n100%|██████████| 64/64 [00:09<00:00, 6.53it/s]", "metrics": { "predict_time": 10.546732175, "total_time": 74.599308 }, "output": "https://replicate.delivery/xezq/TefYpvHO8mkQcEFQQY81mzLjS3kUbdAOo8NLR8Znf06ggJePB/out.png", "started_at": "2024-12-27T12:13:57.797576Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-3phkv55ne24qhxrvzt3oiwkt4a3vng5e7uvbyrtz4pzdekzt4axq", "get": "https://api.replicate.com/v1/predictions/xn4r2sdce5rm80cm10491r5nt4", "cancel": "https://api.replicate.com/v1/predictions/xn4r2sdce5rm80cm10491r5nt4/cancel" }, "version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3" }Generated inUsing seed: 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chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3IDe7z4kjkcg1rme0cm105skgnmhgStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- prompt
- Two pandas in fluffy slippers and bathrobes, lazily munching on bamboo.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{ "prompt": "Two pandas in fluffy slippers and bathrobes, lazily munching on bamboo.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", { input: { prompt: "Two pandas in fluffy slippers and bathrobes, lazily munching on bamboo.", guidance_scale: 5, negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", num_diffusion_steps: 25, 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/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", input={ "prompt": "Two pandas in fluffy slippers and bathrobes, lazily munching on bamboo.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run chenxwh/nova-t2i 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/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", "input": { "prompt": "Two pandas in fluffy slippers and bathrobes, lazily munching on bamboo.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "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": "2024-12-27T12:16:04.333798Z", "created_at": "2024-12-27T12:15:53.984000Z", "data_removed": false, "error": null, "id": "e7z4kjkcg1rme0cm105skgnmhg", "input": { "prompt": "Two pandas in fluffy slippers and bathrobes, lazily munching on bamboo.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }, "logs": "Using seed: 624\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:09, 6.98it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.53it/s]\n 5%|▍ | 3/64 [00:00<00:07, 7.69it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.81it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.72it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.74it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.78it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.76it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.77it/s]\n 16%|█▌ | 10/64 [00:01<00:06, 7.77it/s]\n 17%|█▋ | 11/64 [00:01<00:06, 7.81it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.80it/s]\n 20%|██ | 13/64 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5.53it/s]\n 91%|█████████ | 58/64 [00:08<00:01, 5.51it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.47it/s]\n 94%|█████████▍| 60/64 [00:08<00:00, 5.31it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.23it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.18it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 5.10it/s]\n100%|██████████| 64/64 [00:09<00:00, 4.99it/s]\n100%|██████████| 64/64 [00:09<00:00, 6.55it/s]", "metrics": { "predict_time": 10.343219734, "total_time": 10.349798 }, "output": "https://replicate.delivery/xezq/CVi5So1iVEJxBxd5DnAwwU8vo24wr1kENz8YYbvXqPChMxfJA/out.png", "started_at": "2024-12-27T12:15:53.990579Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-bced6a2bsurx3jihozdreyjdnywrh7ptpsqgngw5oqaxxyqcmjxa", "get": "https://api.replicate.com/v1/predictions/e7z4kjkcg1rme0cm105skgnmhg", "cancel": "https://api.replicate.com/v1/predictions/e7z4kjkcg1rme0cm105skgnmhg/cancel" }, "version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3" }Generated inUsing seed: 624 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:09, 6.98it/s] 3%|▎ | 2/64 [00:00<00:08, 7.53it/s] 5%|▍ | 3/64 [00:00<00:07, 7.69it/s] 6%|▋ | 4/64 [00:00<00:07, 7.81it/s] 8%|▊ | 5/64 [00:00<00:07, 7.72it/s] 9%|▉ | 6/64 [00:00<00:07, 7.74it/s] 11%|█ | 7/64 [00:00<00:07, 7.78it/s] 12%|█▎ | 8/64 [00:01<00:07, 7.76it/s] 14%|█▍ | 9/64 [00:01<00:07, 7.77it/s] 16%|█▌ | 10/64 [00:01<00:06, 7.77it/s] 17%|█▋ | 11/64 [00:01<00:06, 7.81it/s] 19%|█▉ | 12/64 [00:01<00:06, 7.80it/s] 20%|██ | 13/64 [00:01<00:06, 7.76it/s] 22%|██▏ | 14/64 [00:01<00:06, 7.76it/s] 23%|██▎ | 15/64 [00:01<00:06, 7.76it/s] 25%|██▌ | 16/64 [00:02<00:06, 7.76it/s] 27%|██▋ | 17/64 [00:02<00:06, 7.75it/s] 28%|██▊ | 18/64 [00:02<00:05, 7.73it/s] 30%|██▉ | 19/64 [00:02<00:05, 7.72it/s] 31%|███▏ | 20/64 [00:02<00:05, 7.70it/s] 33%|███▎ | 21/64 [00:02<00:05, 7.56it/s] 34%|███▍ | 22/64 [00:02<00:05, 7.46it/s] 36%|███▌ | 23/64 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chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3IDa51pc17dcsrma0cm106bvfteb0StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- prompt
- A photo of llama wearing sunglasses standing on the deck of a spaceship with the Earth in the background.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{ "prompt": "A photo of llama wearing sunglasses standing on the deck of a spaceship with the Earth in the background.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", { input: { prompt: "A photo of llama wearing sunglasses standing on the deck of a spaceship with the Earth in the background.", guidance_scale: 5, negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", num_diffusion_steps: 25, 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/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", input={ "prompt": "A photo of llama wearing sunglasses standing on the deck of a spaceship with the Earth in the background.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run chenxwh/nova-t2i 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/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", "input": { "prompt": "A photo of llama wearing sunglasses standing on the deck of a spaceship with the Earth in the background.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "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": "2024-12-27T12:17:43.102833Z", "created_at": "2024-12-27T12:17:32.518000Z", "data_removed": false, "error": null, "id": "a51pc17dcsrma0cm106bvfteb0", "input": { "prompt": "A photo of llama wearing sunglasses standing on the deck of a spaceship with the Earth in the background.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }, "logs": "Using seed: 17826\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:10, 6.02it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.10it/s]\n 5%|▍ | 3/64 [00:00<00:08, 7.46it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.58it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.66it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.71it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.67it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.73it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.74it/s]\n 16%|█▌ | 10/64 [00:01<00:06, 7.76it/s]\n 17%|█▋ | 11/64 [00:01<00:06, 7.76it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.75it/s]\n 20%|██ | 13/64 [00:01<00:06, 7.75it/s]\n 22%|██▏ | 14/64 [00:01<00:06, 7.77it/s]\n 23%|██▎ | 15/64 [00:01<00:06, 7.76it/s]\n 25%|██▌ | 16/64 [00:02<00:06, 7.75it/s]\n 27%|██▋ | 17/64 [00:02<00:06, 7.76it/s]\n 28%|██▊ | 18/64 [00:02<00:05, 7.75it/s]\n 30%|██▉ | 19/64 [00:02<00:05, 7.73it/s]\n 31%|███▏ | 20/64 [00:02<00:05, 7.65it/s]\n 33%|███▎ | 21/64 [00:02<00:05, 7.53it/s]\n 34%|███▍ | 22/64 [00:02<00:05, 7.45it/s]\n 36%|███▌ | 23/64 [00:03<00:05, 7.38it/s]\n 38%|███▊ | 24/64 [00:03<00:05, 7.33it/s]\n 39%|███▉ | 25/64 [00:03<00:05, 7.30it/s]\n 41%|████ | 26/64 [00:03<00:05, 7.28it/s]\n 42%|████▏ | 27/64 [00:03<00:05, 7.26it/s]\n 44%|████▍ | 28/64 [00:03<00:04, 7.22it/s]\n 45%|████▌ | 29/64 [00:03<00:04, 7.20it/s]\n 47%|████▋ | 30/64 [00:04<00:04, 7.12it/s]\n 48%|████▊ | 31/64 [00:04<00:04, 7.07it/s]\n 50%|█████ | 32/64 [00:04<00:04, 7.02it/s]\n 52%|█████▏ | 33/64 [00:04<00:04, 6.97it/s]\n 53%|█████▎ | 34/64 [00:04<00:04, 6.88it/s]\n 55%|█████▍ | 35/64 [00:04<00:04, 6.85it/s]\n 56%|█████▋ | 36/64 [00:04<00:04, 6.84it/s]\n 58%|█████▊ | 37/64 [00:05<00:03, 6.78it/s]\n 59%|█████▉ | 38/64 [00:05<00:03, 6.75it/s]\n 61%|██████ | 39/64 [00:05<00:03, 6.68it/s]\n 62%|██████▎ | 40/64 [00:05<00:03, 6.62it/s]\n 64%|██████▍ | 41/64 [00:05<00:03, 6.62it/s]\n 66%|██████▌ | 42/64 [00:05<00:03, 6.58it/s]\n 67%|██████▋ | 43/64 [00:05<00:03, 6.40it/s]\n 69%|██████▉ | 44/64 [00:06<00:03, 6.31it/s]\n 70%|███████ | 45/64 [00:06<00:03, 6.22it/s]\n 72%|███████▏ | 46/64 [00:06<00:02, 6.21it/s]\n 73%|███████▎ | 47/64 [00:06<00:02, 6.15it/s]\n 75%|███████▌ | 48/64 [00:06<00:02, 6.07it/s]\n 77%|███████▋ | 49/64 [00:06<00:02, 5.94it/s]\n 78%|███████▊ | 50/64 [00:07<00:02, 5.88it/s]\n 80%|███████▉ | 51/64 [00:07<00:02, 5.81it/s]\n 81%|████████▏ | 52/64 [00:07<00:02, 5.80it/s]\n 83%|████████▎ | 53/64 [00:07<00:01, 5.76it/s]\n 84%|████████▍ | 54/64 [00:07<00:01, 5.76it/s]\n 86%|████████▌ | 55/64 [00:08<00:01, 5.72it/s]\n 88%|████████▊ | 56/64 [00:08<00:01, 5.62it/s]\n 89%|████████▉ | 57/64 [00:08<00:01, 5.56it/s]\n 91%|█████████ | 58/64 [00:08<00:01, 5.54it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.49it/s]\n 94%|█████████▍| 60/64 [00:08<00:00, 5.33it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.25it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.20it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 5.11it/s]\n100%|██████████| 64/64 [00:09<00:00, 5.00it/s]\n100%|██████████| 64/64 [00:09<00:00, 6.56it/s]", "metrics": { "predict_time": 10.574440888, "total_time": 10.584833 }, "output": "https://replicate.delivery/xezq/xK7f5qakOPQIGaDgpf7h4IPj2pky1nrcXJ6iOch2aWpnzEfnA/out.png", "started_at": "2024-12-27T12:17:32.528392Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-7ojrstsxjgkepvstf5igbgl334h4q4vuzlb5bupvt3ds4amiu7na", "get": "https://api.replicate.com/v1/predictions/a51pc17dcsrma0cm106bvfteb0", "cancel": "https://api.replicate.com/v1/predictions/a51pc17dcsrma0cm106bvfteb0/cancel" }, "version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3" }Generated inUsing seed: 17826 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:10, 6.02it/s] 3%|▎ | 2/64 [00:00<00:08, 7.10it/s] 5%|▍ | 3/64 [00:00<00:08, 7.46it/s] 6%|▋ | 4/64 [00:00<00:07, 7.58it/s] 8%|▊ | 5/64 [00:00<00:07, 7.66it/s] 9%|▉ | 6/64 [00:00<00:07, 7.71it/s] 11%|█ | 7/64 [00:00<00:07, 7.67it/s] 12%|█▎ | 8/64 [00:01<00:07, 7.73it/s] 14%|█▍ | 9/64 [00:01<00:07, 7.74it/s] 16%|█▌ | 10/64 [00:01<00:06, 7.76it/s] 17%|█▋ | 11/64 [00:01<00:06, 7.76it/s] 19%|█▉ | 12/64 [00:01<00:06, 7.75it/s] 20%|██ | 13/64 [00:01<00:06, 7.75it/s] 22%|██▏ | 14/64 [00:01<00:06, 7.77it/s] 23%|██▎ | 15/64 [00:01<00:06, 7.76it/s] 25%|██▌ | 16/64 [00:02<00:06, 7.75it/s] 27%|██▋ | 17/64 [00:02<00:06, 7.76it/s] 28%|██▊ | 18/64 [00:02<00:05, 7.75it/s] 30%|██▉ | 19/64 [00:02<00:05, 7.73it/s] 31%|███▏ | 20/64 [00:02<00:05, 7.65it/s] 33%|███▎ | 21/64 [00:02<00:05, 7.53it/s] 34%|███▍ | 22/64 [00:02<00:05, 7.45it/s] 36%|███▌ | 23/64 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6.21it/s] 73%|███████▎ | 47/64 [00:06<00:02, 6.15it/s] 75%|███████▌ | 48/64 [00:06<00:02, 6.07it/s] 77%|███████▋ | 49/64 [00:06<00:02, 5.94it/s] 78%|███████▊ | 50/64 [00:07<00:02, 5.88it/s] 80%|███████▉ | 51/64 [00:07<00:02, 5.81it/s] 81%|████████▏ | 52/64 [00:07<00:02, 5.80it/s] 83%|████████▎ | 53/64 [00:07<00:01, 5.76it/s] 84%|████████▍ | 54/64 [00:07<00:01, 5.76it/s] 86%|████████▌ | 55/64 [00:08<00:01, 5.72it/s] 88%|████████▊ | 56/64 [00:08<00:01, 5.62it/s] 89%|████████▉ | 57/64 [00:08<00:01, 5.56it/s] 91%|█████████ | 58/64 [00:08<00:01, 5.54it/s] 92%|█████████▏| 59/64 [00:08<00:00, 5.49it/s] 94%|█████████▍| 60/64 [00:08<00:00, 5.33it/s] 95%|█████████▌| 61/64 [00:09<00:00, 5.25it/s] 97%|█████████▋| 62/64 [00:09<00:00, 5.20it/s] 98%|█████████▊| 63/64 [00:09<00:00, 5.11it/s] 100%|██████████| 64/64 [00:09<00:00, 5.00it/s] 100%|██████████| 64/64 [00:09<00:00, 6.56it/s]Prediction
chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3ID6kw96fjq3hrma0cm106va82mr4StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- prompt
- a digital artwork of a cat styled in a whimsical fashion. The overall vibe is quirky and artistic.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{ "prompt": "a digital artwork of a cat styled in a whimsical fashion. The overall vibe is quirky and artistic.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", { input: { prompt: "a digital artwork of a cat styled in a whimsical fashion. The overall vibe is quirky and artistic.", guidance_scale: 5, negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", num_diffusion_steps: 25, 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/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", input={ "prompt": "a digital artwork of a cat styled in a whimsical fashion. The overall vibe is quirky and artistic.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run chenxwh/nova-t2i 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/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", "input": { "prompt": "a digital artwork of a cat styled in a whimsical fashion. The overall vibe is quirky and artistic.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "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": "2024-12-27T12:18:09.915622Z", "created_at": "2024-12-27T12:17:59.580000Z", "data_removed": false, "error": null, "id": "6kw96fjq3hrma0cm106va82mr4", "input": { "prompt": "a digital artwork of a cat styled in a whimsical fashion. The overall vibe is quirky and artistic.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }, "logs": "Using seed: 3448\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:09, 6.92it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.49it/s]\n 5%|▍ | 3/64 [00:00<00:07, 7.70it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.77it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.79it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.78it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.79it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.76it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.74it/s]\n 16%|█▌ | 10/64 [00:01<00:06, 7.75it/s]\n 17%|█▋ | 11/64 [00:01<00:06, 7.74it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.75it/s]\n 20%|██ | 13/64 [00:01<00:06, 7.73it/s]\n 22%|██▏ | 14/64 [00:01<00:06, 7.74it/s]\n 23%|██▎ | 15/64 [00:01<00:06, 7.77it/s]\n 25%|██▌ | 16/64 [00:02<00:06, 7.76it/s]\n 27%|██▋ | 17/64 [00:02<00:06, 7.74it/s]\n 28%|██▊ | 18/64 [00:02<00:05, 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[00:05<00:03, 6.56it/s]\n 66%|██████▌ | 42/64 [00:05<00:03, 6.53it/s]\n 67%|██████▋ | 43/64 [00:05<00:03, 6.33it/s]\n 69%|██████▉ | 44/64 [00:06<00:03, 6.24it/s]\n 70%|███████ | 45/64 [00:06<00:03, 6.15it/s]\n 72%|███████▏ | 46/64 [00:06<00:02, 6.14it/s]\n 73%|███████▎ | 47/64 [00:06<00:02, 6.08it/s]\n 75%|███████▌ | 48/64 [00:06<00:02, 5.99it/s]\n 77%|███████▋ | 49/64 [00:06<00:02, 5.88it/s]\n 78%|███████▊ | 50/64 [00:07<00:02, 5.83it/s]\n 80%|███████▉ | 51/64 [00:07<00:02, 5.77it/s]\n 81%|████████▏ | 52/64 [00:07<00:02, 5.75it/s]\n 83%|████████▎ | 53/64 [00:07<00:01, 5.72it/s]\n 84%|████████▍ | 54/64 [00:07<00:01, 5.70it/s]\n 86%|████████▌ | 55/64 [00:08<00:01, 5.64it/s]\n 88%|████████▊ | 56/64 [00:08<00:01, 5.56it/s]\n 89%|████████▉ | 57/64 [00:08<00:01, 5.52it/s]\n 91%|█████████ | 58/64 [00:08<00:01, 5.50it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.47it/s]\n 94%|█████████▍| 60/64 [00:08<00:00, 5.31it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.22it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.17it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 5.09it/s]\n100%|██████████| 64/64 [00:09<00:00, 4.97it/s]\n100%|██████████| 64/64 [00:09<00:00, 6.53it/s]", "metrics": { "predict_time": 10.327737874, "total_time": 10.335622 }, "output": "https://replicate.delivery/xezq/9MyfYocL9TyMYi2qwCMovqNaiSK0oATcjufUeK22hrXCoJePB/out.png", "started_at": "2024-12-27T12:17:59.587884Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-jrm2kj5iece4k2sy363skrq4da22vscmlr5jkucw2l5jnpl5yxpq", "get": "https://api.replicate.com/v1/predictions/6kw96fjq3hrma0cm106va82mr4", "cancel": "https://api.replicate.com/v1/predictions/6kw96fjq3hrma0cm106va82mr4/cancel" }, "version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3" }Generated inUsing seed: 3448 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:09, 6.92it/s] 3%|▎ | 2/64 [00:00<00:08, 7.49it/s] 5%|▍ | 3/64 [00:00<00:07, 7.70it/s] 6%|▋ | 4/64 [00:00<00:07, 7.77it/s] 8%|▊ | 5/64 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83%|████████▎ | 53/64 [00:07<00:01, 5.72it/s] 84%|████████▍ | 54/64 [00:07<00:01, 5.70it/s] 86%|████████▌ | 55/64 [00:08<00:01, 5.64it/s] 88%|████████▊ | 56/64 [00:08<00:01, 5.56it/s] 89%|████████▉ | 57/64 [00:08<00:01, 5.52it/s] 91%|█████████ | 58/64 [00:08<00:01, 5.50it/s] 92%|█████████▏| 59/64 [00:08<00:00, 5.47it/s] 94%|█████████▍| 60/64 [00:08<00:00, 5.31it/s] 95%|█████████▌| 61/64 [00:09<00:00, 5.22it/s] 97%|█████████▋| 62/64 [00:09<00:00, 5.17it/s] 98%|█████████▊| 63/64 [00:09<00:00, 5.09it/s] 100%|██████████| 64/64 [00:09<00:00, 4.97it/s] 100%|██████████| 64/64 [00:09<00:00, 6.53it/s]Prediction
chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3IDswqxm8959xrme0cm107ayzam3rStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- prompt
- A dragon perched majestically on a craggy, smoke-wreathed mountain.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{ "prompt": "A dragon perched majestically on a craggy, smoke-wreathed mountain.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", { input: { prompt: "A dragon perched majestically on a craggy, smoke-wreathed mountain.", guidance_scale: 5, negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", num_diffusion_steps: 25, 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/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", input={ "prompt": "A dragon perched majestically on a craggy, smoke-wreathed mountain.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run chenxwh/nova-t2i 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/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", "input": { "prompt": "A dragon perched majestically on a craggy, smoke-wreathed mountain.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "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": "2024-12-27T12:19:02.888444Z", "created_at": "2024-12-27T12:18:52.367000Z", "data_removed": false, "error": null, "id": "swqxm8959xrme0cm107ayzam3r", "input": { "prompt": "A dragon perched majestically on a craggy, smoke-wreathed mountain.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }, "logs": "Using seed: 22808\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:09, 6.93it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.41it/s]\n 5%|▍ | 3/64 [00:00<00:07, 7.66it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.70it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.70it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.68it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.68it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.68it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.66it/s]\n 16%|█▌ | 10/64 [00:01<00:07, 7.67it/s]\n 17%|█▋ | 11/64 [00:01<00:06, 7.65it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.65it/s]\n 20%|██ | 13/64 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5.43it/s]\n 91%|█████████ | 58/64 [00:08<00:01, 5.45it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.39it/s]\n 94%|█████████▍| 60/64 [00:09<00:00, 5.23it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.14it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.09it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 4.99it/s]\n100%|██████████| 64/64 [00:09<00:00, 4.90it/s]\n100%|██████████| 64/64 [00:09<00:00, 6.44it/s]", "metrics": { "predict_time": 10.514413572, "total_time": 10.521444 }, "output": "https://replicate.delivery/xezq/F8WejJysqMQVJaMlTafRpPm3LXwnJOape9QbjR3laXzspJePB/out.png", "started_at": "2024-12-27T12:18:52.374031Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-6u27z27dgqkluz3y2p3iqnj2rsdt4xfawrr3gf35siplbwxpxupa", "get": "https://api.replicate.com/v1/predictions/swqxm8959xrme0cm107ayzam3r", "cancel": "https://api.replicate.com/v1/predictions/swqxm8959xrme0cm107ayzam3r/cancel" }, "version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3" }Generated inUsing seed: 22808 0%| | 0/64 [00:00<?, ?it/s] 2%|▏ | 1/64 [00:00<00:09, 6.93it/s] 3%|▎ | 2/64 [00:00<00:08, 7.41it/s] 5%|▍ | 3/64 [00:00<00:07, 7.66it/s] 6%|▋ | 4/64 [00:00<00:07, 7.70it/s] 8%|▊ | 5/64 [00:00<00:07, 7.70it/s] 9%|▉ | 6/64 [00:00<00:07, 7.68it/s] 11%|█ | 7/64 [00:00<00:07, 7.68it/s] 12%|█▎ | 8/64 [00:01<00:07, 7.68it/s] 14%|█▍ | 9/64 [00:01<00:07, 7.66it/s] 16%|█▌ | 10/64 [00:01<00:07, 7.67it/s] 17%|█▋ | 11/64 [00:01<00:06, 7.65it/s] 19%|█▉ | 12/64 [00:01<00:06, 7.65it/s] 20%|██ | 13/64 [00:01<00:06, 7.63it/s] 22%|██▏ | 14/64 [00:01<00:06, 7.62it/s] 23%|██▎ | 15/64 [00:01<00:06, 7.60it/s] 25%|██▌ | 16/64 [00:02<00:06, 7.60it/s] 27%|██▋ | 17/64 [00:02<00:06, 7.62it/s] 28%|██▊ | 18/64 [00:02<00:06, 7.60it/s] 30%|██▉ | 19/64 [00:02<00:05, 7.57it/s] 31%|███▏ | 20/64 [00:02<00:05, 7.56it/s] 33%|███▎ | 21/64 [00:02<00:05, 7.42it/s] 34%|███▍ | 22/64 [00:02<00:05, 7.31it/s] 36%|███▌ | 23/64 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6.05it/s] 73%|███████▎ | 47/64 [00:06<00:02, 6.02it/s] 75%|███████▌ | 48/64 [00:06<00:02, 5.92it/s] 77%|███████▋ | 49/64 [00:07<00:02, 5.80it/s] 78%|███████▊ | 50/64 [00:07<00:02, 5.75it/s] 80%|███████▉ | 51/64 [00:07<00:02, 5.70it/s] 81%|████████▏ | 52/64 [00:07<00:02, 5.67it/s] 83%|████████▎ | 53/64 [00:07<00:01, 5.65it/s] 84%|████████▍ | 54/64 [00:07<00:01, 5.62it/s] 86%|████████▌ | 55/64 [00:08<00:01, 5.56it/s] 88%|████████▊ | 56/64 [00:08<00:01, 5.47it/s] 89%|████████▉ | 57/64 [00:08<00:01, 5.43it/s] 91%|█████████ | 58/64 [00:08<00:01, 5.45it/s] 92%|█████████▏| 59/64 [00:08<00:00, 5.39it/s] 94%|█████████▍| 60/64 [00:09<00:00, 5.23it/s] 95%|█████████▌| 61/64 [00:09<00:00, 5.14it/s] 97%|█████████▋| 62/64 [00:09<00:00, 5.09it/s] 98%|█████████▊| 63/64 [00:09<00:00, 4.99it/s] 100%|██████████| 64/64 [00:09<00:00, 4.90it/s] 100%|██████████| 64/64 [00:09<00:00, 6.44it/s]Prediction
chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3IDe1sqtey7g1rmc0cm107bv9rp70StatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- prompt
- a selfie of an old man with a white beard.
- guidance_scale
- 5
- negative_prompt
- low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand
- num_diffusion_steps
- 25
- num_inference_steps
- 64
{ "prompt": "a selfie of an old man with a white beard.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run chenxwh/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", { input: { prompt: "a selfie of an old man with a white beard.", guidance_scale: 5, negative_prompt: "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", num_diffusion_steps: 25, 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/nova-t2i using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "chenxwh/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", input={ "prompt": "a selfie of an old man with a white beard.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 } ) # To access the file URL: print(output.url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output.read())To learn more, take a look at the guide on getting started with Python.
Run chenxwh/nova-t2i 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/nova-t2i:9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3", "input": { "prompt": "a selfie of an old man with a white beard.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "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": "2024-12-27T12:19:44.440011Z", "created_at": "2024-12-27T12:19:33.888000Z", "data_removed": false, "error": null, "id": "e1sqtey7g1rmc0cm107bv9rp70", "input": { "prompt": "a selfie of an old man with a white beard.", "guidance_scale": 5, "negative_prompt": "low quality, deformed, distorted, disfigured, fused fingers, bad anatomy, weird hand", "num_diffusion_steps": 25, "num_inference_steps": 64 }, "logs": "Using seed: 40612\n 0%| | 0/64 [00:00<?, ?it/s]\n 2%|▏ | 1/64 [00:00<00:09, 6.69it/s]\n 3%|▎ | 2/64 [00:00<00:08, 7.25it/s]\n 5%|▍ | 3/64 [00:00<00:08, 7.42it/s]\n 6%|▋ | 4/64 [00:00<00:07, 7.50it/s]\n 8%|▊ | 5/64 [00:00<00:07, 7.50it/s]\n 9%|▉ | 6/64 [00:00<00:07, 7.53it/s]\n 11%|█ | 7/64 [00:00<00:07, 7.58it/s]\n 12%|█▎ | 8/64 [00:01<00:07, 7.59it/s]\n 14%|█▍ | 9/64 [00:01<00:07, 7.58it/s]\n 16%|█▌ | 10/64 [00:01<00:07, 7.56it/s]\n 17%|█▋ | 11/64 [00:01<00:07, 7.56it/s]\n 19%|█▉ | 12/64 [00:01<00:06, 7.55it/s]\n 20%|██ | 13/64 [00:01<00:06, 7.54it/s]\n 22%|██▏ | 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[00:08<00:01, 5.34it/s]\n 92%|█████████▏| 59/64 [00:08<00:00, 5.31it/s]\n 94%|█████████▍| 60/64 [00:09<00:00, 5.16it/s]\n 95%|█████████▌| 61/64 [00:09<00:00, 5.07it/s]\n 97%|█████████▋| 62/64 [00:09<00:00, 5.02it/s]\n 98%|█████████▊| 63/64 [00:09<00:00, 4.93it/s]\n100%|██████████| 64/64 [00:10<00:00, 4.83it/s]\n100%|██████████| 64/64 [00:10<00:00, 6.37it/s]", "metrics": { "predict_time": 10.544868458, "total_time": 10.552011 }, "output": "https://replicate.delivery/xezq/Ag359WDbf6VdNSkrxO6ecLG3kHXEXG6rWv1ROq1EUWng1EfnA/out.png", "started_at": "2024-12-27T12:19:33.895142Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-sw7ehd7x74fwdyr64r5lhrgbyx7gjntwwfg3sn5zi4zsckbyq3aq", "get": "https://api.replicate.com/v1/predictions/e1sqtey7g1rmc0cm107bv9rp70", "cancel": "https://api.replicate.com/v1/predictions/e1sqtey7g1rmc0cm107bv9rp70/cancel" }, "version": "9dbb060cfca8dc11331a76a202d1179c5018f96a84830ce4a402882215e534d3" }Generated inUsing seed: 40612 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