cjwbw
/
tokenflow
Consistent Diffusion Features for Consistent Video Editing
Prediction
cjwbw/tokenflow:d456a26cIDxm4fohlb3gv6e36moshp34oghaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- fps
- 20
- video
- width
- 512
- height
- 512
- n_frames
- 40
- guidance_scale
- 7.5
- diffusion_prompt
- a shiny silver robotic wolf
- inversion_prompt
- num_diffusion_steps
- 50
- num_inversion_steps
- 50
- negative_diffusion_prompt
- ugly, blurry, low res, unrealistic, unaesthetic
{ "fps": 20, "video": "https://replicate.delivery/pbxt/KGcnUKDlfys2uAo8eHbWSE8Pzc17hI5IOGdstViaBvfPJWHY/wolf.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robotic wolf", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", { input: { fps: 20, video: "https://replicate.delivery/pbxt/KGcnUKDlfys2uAo8eHbWSE8Pzc17hI5IOGdstViaBvfPJWHY/wolf.mp4", width: 512, height: 512, n_frames: 40, guidance_scale: 7.5, diffusion_prompt: "a shiny silver robotic wolf", inversion_prompt: "", num_diffusion_steps: 50, num_inversion_steps: 50, negative_diffusion_prompt: "ugly, blurry, low res, unrealistic, unaesthetic" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", input={ "fps": 20, "video": "https://replicate.delivery/pbxt/KGcnUKDlfys2uAo8eHbWSE8Pzc17hI5IOGdstViaBvfPJWHY/wolf.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robotic wolf", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/tokenflow 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": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KGcnUKDlfys2uAo8eHbWSE8Pzc17hI5IOGdstViaBvfPJWHY/wolf.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robotic wolf", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-23T12:51:34.630385Z", "created_at": "2024-01-23T12:47:57.591143Z", "data_removed": false, "error": null, "id": "xm4fohlb3gv6e36moshp34ogha", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KGcnUKDlfys2uAo8eHbWSE8Pzc17hI5IOGdstViaBvfPJWHY/wolf.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robotic wolf", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }, "logs": "Using seed: 60822\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/torchvision/io/video.py:161: UserWarning: The pts_unit 'pts' gives wrong results. Please use pts_unit 'sec'.\nwarnings.warn(\"The pts_unit 'pts' gives wrong results. 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| 39/50 [00:19<00:05, 1.98it/s]\n 80%|████████ | 40/50 [00:19<00:05, 1.98it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 1.98it/s]\n 84%|████████▍ | 42/50 [00:20<00:04, 1.98it/s]\n 86%|████████▌ | 43/50 [00:21<00:03, 1.98it/s]\n 88%|████████▊ | 44/50 [00:21<00:03, 1.98it/s]\n 90%|█████████ | 45/50 [00:22<00:02, 1.98it/s]\n 92%|█████████▏| 46/50 [00:22<00:02, 1.98it/s]\n 94%|█████████▍| 47/50 [00:23<00:01, 1.98it/s]\n 96%|█████████▌| 48/50 [00:23<00:01, 1.98it/s]\n 98%|█████████▊| 49/50 [00:24<00:00, 1.98it/s]\n100%|██████████| 50/50 [00:24<00:00, 1.98it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.02it/s]\nInversion completed!\nNumber of frames for editing: 40\nSampling: 0%| | 0/50 [00:00<?, ?it/s]\nSampling: 2%|▏ | 1/50 [00:02<02:24, 2.95s/it]\nSampling: 4%|▍ | 2/50 [00:05<02:21, 2.94s/it]\nSampling: 6%|▌ | 3/50 [00:08<02:18, 2.94s/it]\nSampling: 8%|▊ | 4/50 [00:11<02:15, 2.94s/it]\nSampling: 10%|█ | 5/50 [00:14<02:12, 2.95s/it]\nSampling: 12%|█▏ | 6/50 [00:17<02:09, 2.94s/it]\nSampling: 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[01:16<01:10, 2.94s/it]\nSampling: 54%|█████▍ | 27/50 [01:19<01:07, 2.94s/it]\nSampling: 56%|█████▌ | 28/50 [01:22<01:04, 2.95s/it]\nSampling: 58%|█████▊ | 29/50 [01:25<01:01, 2.95s/it]\nSampling: 60%|██████ | 30/50 [01:28<00:58, 2.95s/it]\nSampling: 62%|██████▏ | 31/50 [01:31<00:55, 2.95s/it]\nSampling: 64%|██████▍ | 32/50 [01:34<00:53, 2.95s/it]\nSampling: 66%|██████▌ | 33/50 [01:37<00:50, 2.95s/it]\nSampling: 68%|██████▊ | 34/50 [01:40<00:47, 2.95s/it]\nSampling: 70%|███████ | 35/50 [01:43<00:44, 2.95s/it]\nSampling: 72%|███████▏ | 36/50 [01:46<00:41, 2.95s/it]\nSampling: 74%|███████▍ | 37/50 [01:48<00:38, 2.95s/it]\nSampling: 76%|███████▌ | 38/50 [01:51<00:35, 2.95s/it]\nSampling: 78%|███████▊ | 39/50 [01:54<00:32, 2.95s/it]\nSampling: 80%|████████ | 40/50 [01:57<00:29, 2.95s/it]\nSampling: 82%|████████▏ | 41/50 [02:00<00:26, 2.95s/it]\nSampling: 84%|████████▍ | 42/50 [02:03<00:23, 2.96s/it]\nSampling: 86%|████████▌ | 43/50 [02:06<00:20, 2.97s/it]\nSampling: 88%|████████▊ | 44/50 [02:09<00:17, 2.97s/it]\nSampling: 90%|█████████ | 45/50 [02:12<00:14, 2.96s/it]\nSampling: 92%|█████████▏| 46/50 [02:15<00:11, 2.97s/it]\nSampling: 94%|█████████▍| 47/50 [02:18<00:08, 2.97s/it]\nSampling: 96%|█████████▌| 48/50 [02:21<00:05, 2.96s/it]\nSampling: 98%|█████████▊| 49/50 [02:24<00:02, 2.96s/it]\nSampling: 100%|██████████| 50/50 [02:27<00:00, 2.95s/it]\nSampling: 100%|██████████| 50/50 [02:27<00:00, 2.95s/it]\nDone!", "metrics": { "predict_time": 215.7399, "total_time": 217.039242 }, "output": "https://replicate.delivery/pbxt/1Z5jF8MGBw7DNhTSUj8YGSA48d6YsWzDFskNvb2guZZVo1jE/out.mp4", "started_at": "2024-01-23T12:47:58.890485Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xm4fohlb3gv6e36moshp34ogha", "cancel": "https://api.replicate.com/v1/predictions/xm4fohlb3gv6e36moshp34ogha/cancel" }, "version": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728" }
Generated inUsing seed: 60822 /root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/torchvision/io/video.py:161: UserWarning: The pts_unit 'pts' gives wrong results. Please use pts_unit 'sec'. warnings.warn("The pts_unit 'pts' gives wrong results. 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Number of frames for editing: 40 Sampling: 0%| | 0/50 [00:00<?, ?it/s] Sampling: 2%|▏ | 1/50 [00:02<02:24, 2.95s/it] Sampling: 4%|▍ | 2/50 [00:05<02:21, 2.94s/it] Sampling: 6%|▌ | 3/50 [00:08<02:18, 2.94s/it] Sampling: 8%|▊ | 4/50 [00:11<02:15, 2.94s/it] Sampling: 10%|█ | 5/50 [00:14<02:12, 2.95s/it] Sampling: 12%|█▏ | 6/50 [00:17<02:09, 2.94s/it] Sampling: 14%|█▍ | 7/50 [00:20<02:06, 2.94s/it] Sampling: 16%|█▌ | 8/50 [00:23<02:03, 2.94s/it] Sampling: 18%|█▊ | 9/50 [00:26<02:00, 2.94s/it] Sampling: 20%|██ | 10/50 [00:29<01:57, 2.94s/it] Sampling: 22%|██▏ | 11/50 [00:32<01:54, 2.94s/it] Sampling: 24%|██▍ | 12/50 [00:35<01:51, 2.94s/it] Sampling: 26%|██▌ | 13/50 [00:38<01:48, 2.94s/it] Sampling: 28%|██▊ | 14/50 [00:41<01:45, 2.94s/it] Sampling: 30%|███ | 15/50 [00:44<01:43, 2.94s/it] Sampling: 32%|███▏ | 16/50 [00:47<01:40, 2.94s/it] Sampling: 34%|███▍ | 17/50 [00:50<01:37, 2.94s/it] Sampling: 36%|███▌ | 18/50 [00:52<01:34, 2.94s/it] Sampling: 38%|███▊ | 19/50 [00:55<01:31, 2.94s/it] Sampling: 40%|████ | 20/50 [00:58<01:28, 2.94s/it] Sampling: 42%|████▏ | 21/50 [01:01<01:25, 2.94s/it] Sampling: 44%|████▍ | 22/50 [01:04<01:22, 2.94s/it] Sampling: 46%|████▌ | 23/50 [01:07<01:19, 2.95s/it] Sampling: 48%|████▊ | 24/50 [01:10<01:16, 2.95s/it] Sampling: 50%|█████ | 25/50 [01:13<01:13, 2.95s/it] Sampling: 52%|█████▏ | 26/50 [01:16<01:10, 2.94s/it] Sampling: 54%|█████▍ | 27/50 [01:19<01:07, 2.94s/it] Sampling: 56%|█████▌ | 28/50 [01:22<01:04, 2.95s/it] Sampling: 58%|█████▊ | 29/50 [01:25<01:01, 2.95s/it] Sampling: 60%|██████ | 30/50 [01:28<00:58, 2.95s/it] Sampling: 62%|██████▏ | 31/50 [01:31<00:55, 2.95s/it] Sampling: 64%|██████▍ | 32/50 [01:34<00:53, 2.95s/it] Sampling: 66%|██████▌ | 33/50 [01:37<00:50, 2.95s/it] Sampling: 68%|██████▊ | 34/50 [01:40<00:47, 2.95s/it] Sampling: 70%|███████ | 35/50 [01:43<00:44, 2.95s/it] Sampling: 72%|███████▏ | 36/50 [01:46<00:41, 2.95s/it] Sampling: 74%|███████▍ | 37/50 [01:48<00:38, 2.95s/it] Sampling: 76%|███████▌ | 38/50 [01:51<00:35, 2.95s/it] Sampling: 78%|███████▊ | 39/50 [01:54<00:32, 2.95s/it] Sampling: 80%|████████ | 40/50 [01:57<00:29, 2.95s/it] Sampling: 82%|████████▏ | 41/50 [02:00<00:26, 2.95s/it] Sampling: 84%|████████▍ | 42/50 [02:03<00:23, 2.96s/it] Sampling: 86%|████████▌ | 43/50 [02:06<00:20, 2.97s/it] Sampling: 88%|████████▊ | 44/50 [02:09<00:17, 2.97s/it] Sampling: 90%|█████████ | 45/50 [02:12<00:14, 2.96s/it] Sampling: 92%|█████████▏| 46/50 [02:15<00:11, 2.97s/it] Sampling: 94%|█████████▍| 47/50 [02:18<00:08, 2.97s/it] Sampling: 96%|█████████▌| 48/50 [02:21<00:05, 2.96s/it] Sampling: 98%|█████████▊| 49/50 [02:24<00:02, 2.96s/it] Sampling: 100%|██████████| 50/50 [02:27<00:00, 2.95s/it] Sampling: 100%|██████████| 50/50 [02:27<00:00, 2.95s/it] Done!
Prediction
cjwbw/tokenflow:d456a26cIDg77x35lban5n66a6b3gd6mnekqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- fps
- 20
- video
- width
- 512
- height
- 512
- n_frames
- 40
- guidance_scale
- 7.5
- diffusion_prompt
- a shiny silver robot doing the floss dance on Mars
- inversion_prompt
- num_diffusion_steps
- 50
- num_inversion_steps
- 50
- negative_diffusion_prompt
- ugly, blurry, low res, unrealistic, unaesthetic
{ "fps": 20, "video": "https://replicate.delivery/pbxt/KHC7KXbwWKEPQVLfnOq9akgsSvdW8Meo4V2lJY1VLfMbVDo9/test.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robot doing the floss dance on Mars", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", { input: { fps: 20, video: "https://replicate.delivery/pbxt/KHC7KXbwWKEPQVLfnOq9akgsSvdW8Meo4V2lJY1VLfMbVDo9/test.mp4", width: 512, height: 512, n_frames: 40, guidance_scale: 7.5, diffusion_prompt: "a shiny silver robot doing the floss dance on Mars", inversion_prompt: "", num_diffusion_steps: 50, num_inversion_steps: 50, negative_diffusion_prompt: "ugly, blurry, low res, unrealistic, unaesthetic" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", input={ "fps": 20, "video": "https://replicate.delivery/pbxt/KHC7KXbwWKEPQVLfnOq9akgsSvdW8Meo4V2lJY1VLfMbVDo9/test.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robot doing the floss dance on Mars", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/tokenflow 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": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KHC7KXbwWKEPQVLfnOq9akgsSvdW8Meo4V2lJY1VLfMbVDo9/test.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robot doing the floss dance on Mars", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-23T12:54:31.427985Z", "created_at": "2024-01-23T12:50:36.268062Z", "data_removed": false, "error": null, "id": "g77x35lban5n66a6b3gd6mnekq", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KHC7KXbwWKEPQVLfnOq9akgsSvdW8Meo4V2lJY1VLfMbVDo9/test.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a shiny silver robot doing the floss dance on Mars", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }, "logs": "Using seed: 51873\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:24, 1.99it/s]\n 4%|▍ | 2/50 [00:01<00:23, 2.00it/s]\n 6%|▌ | 3/50 [00:01<00:23, 2.01it/s]\n 8%|▊ | 4/50 [00:01<00:22, 2.01it/s]\n 10%|█ | 5/50 [00:02<00:22, 2.01it/s]\n 12%|█▏ | 6/50 [00:02<00:21, 2.01it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 2.01it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.01it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 2.01it/s]\n 20%|██ | 10/50 [00:04<00:19, 2.01it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 2.00it/s]\n 24%|██▍ | 12/50 [00:05<00:18, 2.01it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 2.01it/s]\n 28%|██▊ | 14/50 [00:06<00:17, 2.01it/s]\n 30%|███ | 15/50 [00:07<00:17, 2.01it/s]\n 32%|███▏ | 16/50 [00:07<00:16, 2.00it/s]\n 34%|███▍ | 17/50 [00:08<00:16, 2.01it/s]\n 36%|███▌ | 18/50 [00:08<00:15, 2.01it/s]\n 38%|███▊ | 19/50 [00:09<00:15, 2.01it/s]\n 40%|████ | 20/50 [00:09<00:14, 2.01it/s]\n 42%|████▏ | 21/50 [00:10<00:14, 2.01it/s]\n 44%|████▍ | 22/50 [00:10<00:13, 2.01it/s]\n 46%|████▌ | 23/50 [00:11<00:13, 2.01it/s]\n 48%|████▊ | 24/50 [00:11<00:12, 2.01it/s]\n 50%|█████ | 25/50 [00:12<00:12, 2.00it/s]\n 52%|█████▏ | 26/50 [00:12<00:11, 2.00it/s]\n 54%|█████▍ | 27/50 [00:13<00:11, 2.00it/s]\n 56%|█████▌ | 28/50 [00:13<00:10, 2.01it/s]\n 58%|█████▊ | 29/50 [00:14<00:10, 2.01it/s]\n 60%|██████ | 30/50 [00:14<00:09, 2.00it/s]\n 62%|██████▏ | 31/50 [00:15<00:09, 2.00it/s]\n 64%|██████▍ | 32/50 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| 2/50 [00:00<00:16, 2.98it/s]\n 6%|▌ | 3/50 [00:01<00:19, 2.44it/s]\n 8%|▊ | 4/50 [00:01<00:20, 2.25it/s]\n 10%|█ | 5/50 [00:02<00:20, 2.15it/s]\n 12%|█▏ | 6/50 [00:02<00:20, 2.10it/s]\n 14%|█▍ | 7/50 [00:03<00:20, 2.07it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.05it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 2.04it/s]\n 20%|██ | 10/50 [00:04<00:19, 2.03it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 2.02it/s]\n 24%|██▍ | 12/50 [00:05<00:18, 2.02it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 2.01it/s]\n 28%|██▊ | 14/50 [00:06<00:17, 2.01it/s]\n 30%|███ | 15/50 [00:07<00:17, 2.01it/s]\n 32%|███▏ | 16/50 [00:07<00:16, 2.01it/s]\n 34%|███▍ | 17/50 [00:08<00:16, 2.01it/s]\n 36%|███▌ | 18/50 [00:08<00:15, 2.01it/s]\n 38%|███▊ | 19/50 [00:09<00:15, 2.01it/s]\n 40%|████ | 20/50 [00:09<00:14, 2.01it/s]\n 42%|████▏ | 21/50 [00:10<00:14, 2.01it/s]\n 44%|████▍ | 22/50 [00:10<00:13, 2.01it/s]\n 46%|████▌ | 23/50 [00:11<00:13, 2.00it/s]\n 48%|████▊ | 24/50 [00:11<00:12, 2.00it/s]\n 50%|█████ | 25/50 [00:12<00:12, 2.00it/s]\n 52%|█████▏ | 26/50 [00:12<00:11, 2.00it/s]\n 54%|█████▍ | 27/50 [00:13<00:11, 2.00it/s]\n 56%|█████▌ | 28/50 [00:13<00:10, 2.01it/s]\n 58%|█████▊ | 29/50 [00:14<00:10, 2.01it/s]\n 60%|██████ | 30/50 [00:14<00:09, 2.01it/s]\n 62%|██████▏ | 31/50 [00:15<00:09, 2.01it/s]\n 64%|██████▍ | 32/50 [00:15<00:08, 2.01it/s]\n 66%|██████▌ | 33/50 [00:16<00:08, 2.01it/s]\n 68%|██████▊ | 34/50 [00:16<00:07, 2.01it/s]\n 70%|███████ | 35/50 [00:17<00:07, 2.01it/s]\n 72%|███████▏ | 36/50 [00:17<00:06, 2.01it/s]\n 74%|███████▍ | 37/50 [00:18<00:06, 2.01it/s]\n 76%|███████▌ | 38/50 [00:18<00:05, 2.01it/s]\n 78%|███████▊ | 39/50 [00:19<00:05, 2.01it/s]\n 80%|████████ | 40/50 [00:19<00:04, 2.01it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 2.01it/s]\n 84%|████████▍ | 42/50 [00:20<00:03, 2.01it/s]\n 86%|████████▌ | 43/50 [00:21<00:03, 2.01it/s]\n 88%|████████▊ | 44/50 [00:21<00:02, 2.01it/s]\n 90%|█████████ | 45/50 [00:22<00:02, 2.01it/s]\n 92%|█████████▏| 46/50 [00:22<00:01, 2.01it/s]\n 94%|█████████▍| 47/50 [00:23<00:01, 2.01it/s]\n 96%|█████████▌| 48/50 [00:23<00:00, 2.01it/s]\n 98%|█████████▊| 49/50 [00:24<00:00, 2.00it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.00it/s]\n100%|██████████| 50/50 [00:24<00:00, 2.04it/s]\nInversion completed!\nNumber of frames for editing: 32\nSampling: 0%| | 0/50 [00:00<?, ?it/s]\nSampling: 2%|▏ | 1/50 [00:02<01:48, 2.22s/it]\nSampling: 4%|▍ | 2/50 [00:04<01:46, 2.21s/it]\nSampling: 6%|▌ | 3/50 [00:06<01:44, 2.21s/it]\nSampling: 8%|▊ | 4/50 [00:08<01:41, 2.21s/it]\nSampling: 10%|█ | 5/50 [00:11<01:39, 2.21s/it]\nSampling: 12%|█▏ | 6/50 [00:13<01:37, 2.21s/it]\nSampling: 14%|█▍ | 7/50 [00:15<01:35, 2.21s/it]\nSampling: 16%|█▌ | 8/50 [00:17<01:32, 2.21s/it]\nSampling: 18%|█▊ | 9/50 [00:19<01:30, 2.21s/it]\nSampling: 20%|██ | 10/50 [00:22<01:28, 2.21s/it]\nSampling: 22%|██▏ | 11/50 [00:24<01:26, 2.21s/it]\nSampling: 24%|██▍ | 12/50 [00:26<01:24, 2.22s/it]\nSampling: 26%|██▌ | 13/50 [00:28<01:21, 2.22s/it]\nSampling: 28%|██▊ | 14/50 [00:31<01:19, 2.22s/it]\nSampling: 30%|███ | 15/50 [00:33<01:17, 2.22s/it]\nSampling: 32%|███▏ | 16/50 [00:35<01:15, 2.22s/it]\nSampling: 34%|███▍ | 17/50 [00:37<01:13, 2.22s/it]\nSampling: 36%|███▌ | 18/50 [00:39<01:10, 2.21s/it]\nSampling: 38%|███▊ | 19/50 [00:42<01:08, 2.22s/it]\nSampling: 40%|████ | 20/50 [00:44<01:06, 2.22s/it]\nSampling: 42%|████▏ | 21/50 [00:46<01:04, 2.22s/it]\nSampling: 44%|████▍ | 22/50 [00:48<01:02, 2.22s/it]\nSampling: 46%|████▌ | 23/50 [00:50<00:59, 2.22s/it]\nSampling: 48%|████▊ | 24/50 [00:53<00:57, 2.21s/it]\nSampling: 50%|█████ | 25/50 [00:55<00:55, 2.21s/it]\nSampling: 52%|█████▏ | 26/50 [00:57<00:53, 2.22s/it]\nSampling: 54%|█████▍ | 27/50 [00:59<00:50, 2.21s/it]\nSampling: 56%|█████▌ | 28/50 [01:02<00:48, 2.21s/it]\nSampling: 58%|█████▊ | 29/50 [01:04<00:46, 2.21s/it]\nSampling: 60%|██████ | 30/50 [01:06<00:44, 2.21s/it]\nSampling: 62%|██████▏ | 31/50 [01:08<00:42, 2.21s/it]\nSampling: 64%|██████▍ | 32/50 [01:10<00:39, 2.22s/it]\nSampling: 66%|██████▌ | 33/50 [01:13<00:37, 2.22s/it]\nSampling: 68%|██████▊ | 34/50 [01:15<00:35, 2.22s/it]\nSampling: 70%|███████ | 35/50 [01:17<00:33, 2.22s/it]\nSampling: 72%|███████▏ | 36/50 [01:19<00:31, 2.22s/it]\nSampling: 74%|███████▍ | 37/50 [01:21<00:28, 2.22s/it]\nSampling: 76%|███████▌ | 38/50 [01:24<00:26, 2.22s/it]\nSampling: 78%|███████▊ | 39/50 [01:26<00:24, 2.22s/it]\nSampling: 80%|████████ | 40/50 [01:28<00:22, 2.22s/it]\nSampling: 82%|████████▏ | 41/50 [01:30<00:19, 2.22s/it]\nSampling: 84%|████████▍ | 42/50 [01:33<00:17, 2.22s/it]\nSampling: 86%|████████▌ | 43/50 [01:35<00:15, 2.22s/it]\nSampling: 88%|████████▊ | 44/50 [01:37<00:13, 2.22s/it]\nSampling: 90%|█████████ | 45/50 [01:39<00:11, 2.22s/it]\nSampling: 92%|█████████▏| 46/50 [01:41<00:08, 2.22s/it]\nSampling: 94%|█████████▍| 47/50 [01:44<00:06, 2.22s/it]\nSampling: 96%|█████████▌| 48/50 [01:46<00:04, 2.22s/it]\nSampling: 98%|█████████▊| 49/50 [01:48<00:02, 2.22s/it]\nSampling: 100%|██████████| 50/50 [01:50<00:00, 2.22s/it]\nSampling: 100%|██████████| 50/50 [01:50<00:00, 2.22s/it]\nDone!", "metrics": { "predict_time": 175.176738, "total_time": 235.159923 }, "output": "https://replicate.delivery/pbxt/ciXSoBxyX2oCDVBXwqeMAkXvf2eQwg64MNic3KfjQUYZQa9IB/out.mp4", "started_at": "2024-01-23T12:51:36.251247Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/g77x35lban5n66a6b3gd6mnekq", "cancel": "https://api.replicate.com/v1/predictions/g77x35lban5n66a6b3gd6mnekq/cancel" }, "version": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728" }
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Number of frames for editing: 32 Sampling: 0%| | 0/50 [00:00<?, ?it/s] Sampling: 2%|▏ | 1/50 [00:02<01:48, 2.22s/it] Sampling: 4%|▍ | 2/50 [00:04<01:46, 2.21s/it] Sampling: 6%|▌ | 3/50 [00:06<01:44, 2.21s/it] Sampling: 8%|▊ | 4/50 [00:08<01:41, 2.21s/it] Sampling: 10%|█ | 5/50 [00:11<01:39, 2.21s/it] Sampling: 12%|█▏ | 6/50 [00:13<01:37, 2.21s/it] Sampling: 14%|█▍ | 7/50 [00:15<01:35, 2.21s/it] Sampling: 16%|█▌ | 8/50 [00:17<01:32, 2.21s/it] Sampling: 18%|█▊ | 9/50 [00:19<01:30, 2.21s/it] Sampling: 20%|██ | 10/50 [00:22<01:28, 2.21s/it] Sampling: 22%|██▏ | 11/50 [00:24<01:26, 2.21s/it] Sampling: 24%|██▍ | 12/50 [00:26<01:24, 2.22s/it] Sampling: 26%|██▌ | 13/50 [00:28<01:21, 2.22s/it] Sampling: 28%|██▊ | 14/50 [00:31<01:19, 2.22s/it] Sampling: 30%|███ | 15/50 [00:33<01:17, 2.22s/it] Sampling: 32%|███▏ | 16/50 [00:35<01:15, 2.22s/it] Sampling: 34%|███▍ | 17/50 [00:37<01:13, 2.22s/it] Sampling: 36%|███▌ | 18/50 [00:39<01:10, 2.21s/it] Sampling: 38%|███▊ | 19/50 [00:42<01:08, 2.22s/it] Sampling: 40%|████ | 20/50 [00:44<01:06, 2.22s/it] Sampling: 42%|████▏ | 21/50 [00:46<01:04, 2.22s/it] Sampling: 44%|████▍ | 22/50 [00:48<01:02, 2.22s/it] Sampling: 46%|████▌ | 23/50 [00:50<00:59, 2.22s/it] Sampling: 48%|████▊ | 24/50 [00:53<00:57, 2.21s/it] Sampling: 50%|█████ | 25/50 [00:55<00:55, 2.21s/it] Sampling: 52%|█████▏ | 26/50 [00:57<00:53, 2.22s/it] Sampling: 54%|█████▍ | 27/50 [00:59<00:50, 2.21s/it] Sampling: 56%|█████▌ | 28/50 [01:02<00:48, 2.21s/it] Sampling: 58%|█████▊ | 29/50 [01:04<00:46, 2.21s/it] Sampling: 60%|██████ | 30/50 [01:06<00:44, 2.21s/it] Sampling: 62%|██████▏ | 31/50 [01:08<00:42, 2.21s/it] Sampling: 64%|██████▍ | 32/50 [01:10<00:39, 2.22s/it] Sampling: 66%|██████▌ | 33/50 [01:13<00:37, 2.22s/it] Sampling: 68%|██████▊ | 34/50 [01:15<00:35, 2.22s/it] Sampling: 70%|███████ | 35/50 [01:17<00:33, 2.22s/it] Sampling: 72%|███████▏ | 36/50 [01:19<00:31, 2.22s/it] Sampling: 74%|███████▍ | 37/50 [01:21<00:28, 2.22s/it] Sampling: 76%|███████▌ | 38/50 [01:24<00:26, 2.22s/it] Sampling: 78%|███████▊ | 39/50 [01:26<00:24, 2.22s/it] Sampling: 80%|████████ | 40/50 [01:28<00:22, 2.22s/it] Sampling: 82%|████████▏ | 41/50 [01:30<00:19, 2.22s/it] Sampling: 84%|████████▍ | 42/50 [01:33<00:17, 2.22s/it] Sampling: 86%|████████▌ | 43/50 [01:35<00:15, 2.22s/it] Sampling: 88%|████████▊ | 44/50 [01:37<00:13, 2.22s/it] Sampling: 90%|█████████ | 45/50 [01:39<00:11, 2.22s/it] Sampling: 92%|█████████▏| 46/50 [01:41<00:08, 2.22s/it] Sampling: 94%|█████████▍| 47/50 [01:44<00:06, 2.22s/it] Sampling: 96%|█████████▌| 48/50 [01:46<00:04, 2.22s/it] Sampling: 98%|█████████▊| 49/50 [01:48<00:02, 2.22s/it] Sampling: 100%|██████████| 50/50 [01:50<00:00, 2.22s/it] Sampling: 100%|██████████| 50/50 [01:50<00:00, 2.22s/it] Done!
Prediction
cjwbw/tokenflow:d456a26cIDmsm4lilblwh3f7s5haf3gf7d24StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- fps
- 20
- video
- width
- 512
- height
- 512
- n_frames
- 40
- guidance_scale
- 7.5
- diffusion_prompt
- a marble sculpture of a woman running, Venus de Milo
- inversion_prompt
- num_diffusion_steps
- 50
- num_inversion_steps
- 50
- negative_diffusion_prompt
- ugly, blurry, low res, unrealistic, unaesthetic
{ "fps": 20, "video": "https://replicate.delivery/pbxt/KHC9ogpXAwlDf1vM7u8melD8QuU3tTsUsoLFMUwEccx3ZMRT/woman-running.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a marble sculpture of a woman running, Venus de Milo", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", { input: { fps: 20, video: "https://replicate.delivery/pbxt/KHC9ogpXAwlDf1vM7u8melD8QuU3tTsUsoLFMUwEccx3ZMRT/woman-running.mp4", width: 512, height: 512, n_frames: 40, guidance_scale: 7.5, diffusion_prompt: "a marble sculpture of a woman running, Venus de Milo", inversion_prompt: "", num_diffusion_steps: 50, num_inversion_steps: 50, negative_diffusion_prompt: "ugly, blurry, low res, unrealistic, unaesthetic" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", input={ "fps": 20, "video": "https://replicate.delivery/pbxt/KHC9ogpXAwlDf1vM7u8melD8QuU3tTsUsoLFMUwEccx3ZMRT/woman-running.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a marble sculpture of a woman running, Venus de Milo", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/tokenflow 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": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KHC9ogpXAwlDf1vM7u8melD8QuU3tTsUsoLFMUwEccx3ZMRT/woman-running.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a marble sculpture of a woman running, Venus de Milo", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-23T12:56:55.939586Z", "created_at": "2024-01-23T12:53:14.115204Z", "data_removed": false, "error": null, "id": "msm4lilblwh3f7s5haf3gf7d24", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KHC9ogpXAwlDf1vM7u8melD8QuU3tTsUsoLFMUwEccx3ZMRT/woman-running.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "a marble sculpture of a woman running, Venus de Milo", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }, "logs": "Using seed: 4067\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:25, 1.95it/s]\n 4%|▍ | 2/50 [00:01<00:24, 1.96it/s]\n 6%|▌ | 3/50 [00:01<00:23, 1.96it/s]\n 8%|▊ | 4/50 [00:02<00:23, 1.96it/s]\n 10%|█ | 5/50 [00:02<00:22, 1.96it/s]\n 12%|█▏ | 6/50 [00:03<00:22, 1.96it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 1.96it/s]\n 16%|█▌ | 8/50 [00:04<00:21, 1.96it/s]\n 18%|█▊ | 9/50 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4%|▍ | 2/50 [00:00<00:16, 2.91it/s]\n 6%|▌ | 3/50 [00:01<00:19, 2.39it/s]\n 8%|▊ | 4/50 [00:01<00:20, 2.20it/s]\n 10%|█ | 5/50 [00:02<00:21, 2.11it/s]\n 12%|█▏ | 6/50 [00:02<00:21, 2.06it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 2.03it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.01it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 2.00it/s]\n 20%|██ | 10/50 [00:04<00:20, 1.99it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 1.98it/s]\n 24%|██▍ | 12/50 [00:05<00:19, 1.98it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 1.97it/s]\n 28%|██▊ | 14/50 [00:06<00:18, 1.97it/s]\n 30%|███ | 15/50 [00:07<00:17, 1.97it/s]\n 32%|███▏ | 16/50 [00:07<00:17, 1.97it/s]\n 34%|███▍ | 17/50 [00:08<00:16, 1.97it/s]\n 36%|███▌ | 18/50 [00:08<00:16, 1.97it/s]\n 38%|███▊ | 19/50 [00:09<00:15, 1.97it/s]\n 40%|████ | 20/50 [00:09<00:15, 1.97it/s]\n 42%|████▏ | 21/50 [00:10<00:14, 1.96it/s]\n 44%|████▍ | 22/50 [00:10<00:14, 1.96it/s]\n 46%|████▌ | 23/50 [00:11<00:13, 1.96it/s]\n 48%|████▊ | 24/50 [00:11<00:13, 1.96it/s]\n 50%|█████ | 25/50 [00:12<00:12, 1.96it/s]\n 52%|█████▏ | 26/50 [00:12<00:12, 1.96it/s]\n 54%|█████▍ | 27/50 [00:13<00:11, 1.96it/s]\n 56%|█████▌ | 28/50 [00:13<00:11, 1.96it/s]\n 58%|█████▊ | 29/50 [00:14<00:10, 1.96it/s]\n 60%|██████ | 30/50 [00:14<00:10, 1.96it/s]\n 62%|██████▏ | 31/50 [00:15<00:09, 1.96it/s]\n 64%|██████▍ | 32/50 [00:15<00:09, 1.96it/s]\n 66%|██████▌ | 33/50 [00:16<00:08, 1.96it/s]\n 68%|██████▊ | 34/50 [00:16<00:08, 1.96it/s]\n 70%|███████ | 35/50 [00:17<00:07, 1.96it/s]\n 72%|███████▏ | 36/50 [00:17<00:07, 1.96it/s]\n 74%|███████▍ | 37/50 [00:18<00:06, 1.96it/s]\n 76%|███████▌ | 38/50 [00:18<00:06, 1.96it/s]\n 78%|███████▊ | 39/50 [00:19<00:05, 1.96it/s]\n 80%|████████ | 40/50 [00:19<00:05, 1.96it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 1.96it/s]\n 84%|████████▍ | 42/50 [00:20<00:04, 1.96it/s]\n 86%|████████▌ | 43/50 [00:21<00:03, 1.96it/s]\n 88%|████████▊ | 44/50 [00:22<00:03, 1.96it/s]\n 90%|█████████ | 45/50 [00:22<00:02, 1.96it/s]\n 92%|█████████▏| 46/50 [00:23<00:02, 1.96it/s]\n 94%|█████████▍| 47/50 [00:23<00:01, 1.96it/s]\n 96%|█████████▌| 48/50 [00:24<00:01, 1.96it/s]\n 98%|█████████▊| 49/50 [00:24<00:00, 1.96it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.96it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.99it/s]\nInversion completed!\nNumber of frames for editing: 40\nSampling: 0%| | 0/50 [00:00<?, ?it/s]\nSampling: 2%|▏ | 1/50 [00:02<02:26, 2.99s/it]\nSampling: 4%|▍ | 2/50 [00:05<02:23, 2.99s/it]\nSampling: 6%|▌ | 3/50 [00:08<02:20, 2.99s/it]\nSampling: 8%|▊ | 4/50 [00:11<02:17, 2.99s/it]\nSampling: 10%|█ | 5/50 [00:14<02:14, 2.98s/it]\nSampling: 12%|█▏ | 6/50 [00:17<02:11, 2.98s/it]\nSampling: 14%|█▍ | 7/50 [00:20<02:08, 2.98s/it]\nSampling: 16%|█▌ | 8/50 [00:23<02:05, 2.98s/it]\nSampling: 18%|█▊ | 9/50 [00:26<02:02, 2.98s/it]\nSampling: 20%|██ | 10/50 [00:29<01:59, 2.98s/it]\nSampling: 22%|██▏ | 11/50 [00:32<01:56, 2.98s/it]\nSampling: 24%|██▍ | 12/50 [00:35<01:53, 2.98s/it]\nSampling: 26%|██▌ | 13/50 [00:38<01:50, 2.98s/it]\nSampling: 28%|██▊ | 14/50 [00:41<01:47, 2.98s/it]\nSampling: 30%|███ | 15/50 [00:44<01:44, 2.98s/it]\nSampling: 32%|███▏ | 16/50 [00:47<01:41, 2.98s/it]\nSampling: 34%|███▍ | 17/50 [00:50<01:38, 2.98s/it]\nSampling: 36%|███▌ | 18/50 [00:53<01:35, 2.98s/it]\nSampling: 38%|███▊ | 19/50 [00:56<01:32, 2.98s/it]\nSampling: 40%|████ | 20/50 [00:59<01:29, 2.98s/it]\nSampling: 42%|████▏ | 21/50 [01:02<01:26, 2.98s/it]\nSampling: 44%|████▍ | 22/50 [01:05<01:23, 2.98s/it]\nSampling: 46%|████▌ | 23/50 [01:08<01:20, 2.98s/it]\nSampling: 48%|████▊ | 24/50 [01:11<01:17, 2.98s/it]\nSampling: 50%|█████ | 25/50 [01:14<01:14, 2.98s/it]\nSampling: 52%|█████▏ | 26/50 [01:17<01:11, 2.98s/it]\nSampling: 54%|█████▍ | 27/50 [01:20<01:08, 2.98s/it]\nSampling: 56%|█████▌ | 28/50 [01:23<01:05, 2.98s/it]\nSampling: 58%|█████▊ | 29/50 [01:26<01:02, 2.98s/it]\nSampling: 60%|██████ | 30/50 [01:29<00:59, 2.98s/it]\nSampling: 62%|██████▏ | 31/50 [01:32<00:56, 2.97s/it]\nSampling: 64%|██████▍ | 32/50 [01:35<00:53, 2.97s/it]\nSampling: 66%|██████▌ | 33/50 [01:38<00:50, 2.98s/it]\nSampling: 68%|██████▊ | 34/50 [01:41<00:47, 2.97s/it]\nSampling: 70%|███████ | 35/50 [01:44<00:44, 2.98s/it]\nSampling: 72%|███████▏ | 36/50 [01:47<00:41, 2.98s/it]\nSampling: 74%|███████▍ | 37/50 [01:50<00:38, 2.98s/it]\nSampling: 76%|███████▌ | 38/50 [01:53<00:35, 2.98s/it]\nSampling: 78%|███████▊ | 39/50 [01:56<00:32, 2.98s/it]\nSampling: 80%|████████ | 40/50 [01:59<00:29, 2.98s/it]\nSampling: 82%|████████▏ | 41/50 [02:02<00:26, 2.98s/it]\nSampling: 84%|████████▍ | 42/50 [02:05<00:23, 2.98s/it]\nSampling: 86%|████████▌ | 43/50 [02:08<00:20, 2.98s/it]\nSampling: 88%|████████▊ | 44/50 [02:11<00:17, 2.98s/it]\nSampling: 90%|█████████ | 45/50 [02:13<00:14, 2.98s/it]\nSampling: 92%|█████████▏| 46/50 [02:16<00:11, 2.98s/it]\nSampling: 94%|█████████▍| 47/50 [02:19<00:08, 2.98s/it]\nSampling: 96%|█████████▌| 48/50 [02:22<00:05, 2.98s/it]\nSampling: 98%|█████████▊| 49/50 [02:25<00:02, 2.98s/it]\nSampling: 100%|██████████| 50/50 [02:28<00:00, 2.98s/it]\nSampling: 100%|██████████| 50/50 [02:28<00:00, 2.98s/it]\nDone!", "metrics": { "predict_time": 221.492871, "total_time": 221.824382 }, "output": "https://replicate.delivery/pbxt/FEjd8kM09b6uPFcJvWK2zDPUulBtWTkeND8tzjYiJTkLTrHJA/out.mp4", "started_at": "2024-01-23T12:53:14.446715Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/msm4lilblwh3f7s5haf3gf7d24", "cancel": "https://api.replicate.com/v1/predictions/msm4lilblwh3f7s5haf3gf7d24/cancel" }, "version": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728" }
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Prediction
cjwbw/tokenflow:d456a26cIDbtogko3bewjnkplzkbx2yjevz4StatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- fps
- 20
- video
- width
- 512
- height
- 512
- n_frames
- 40
- guidance_scale
- 7.5
- diffusion_prompt
- slicing a piece of salmon
- inversion_prompt
- num_diffusion_steps
- 50
- num_inversion_steps
- 50
- negative_diffusion_prompt
- ugly, blurry, low res, unrealistic, unaesthetic
{ "fps": 20, "video": "https://replicate.delivery/pbxt/KHCDuXUV4OrOmMtk7sukh8Rjh0fkf5za0tUeFyAwDchQpENW/cutting_bread.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "slicing a piece of salmon", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }
Install Replicate’s Node.js client library:npm install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", { input: { fps: 20, video: "https://replicate.delivery/pbxt/KHCDuXUV4OrOmMtk7sukh8Rjh0fkf5za0tUeFyAwDchQpENW/cutting_bread.mp4", width: 512, height: 512, n_frames: 40, guidance_scale: 7.5, diffusion_prompt: "slicing a piece of salmon", inversion_prompt: "", num_diffusion_steps: 50, num_inversion_steps: 50, negative_diffusion_prompt: "ugly, blurry, low res, unrealistic, unaesthetic" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Import the client:import replicate
Run cjwbw/tokenflow using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "cjwbw/tokenflow:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", input={ "fps": 20, "video": "https://replicate.delivery/pbxt/KHCDuXUV4OrOmMtk7sukh8Rjh0fkf5za0tUeFyAwDchQpENW/cutting_bread.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "slicing a piece of salmon", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Set theREPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run cjwbw/tokenflow 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": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KHCDuXUV4OrOmMtk7sukh8Rjh0fkf5za0tUeFyAwDchQpENW/cutting_bread.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "slicing a piece of salmon", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-23T13:01:13.922826Z", "created_at": "2024-01-23T12:57:33.198812Z", "data_removed": false, "error": null, "id": "btogko3bewjnkplzkbx2yjevz4", "input": { "fps": 20, "video": "https://replicate.delivery/pbxt/KHCDuXUV4OrOmMtk7sukh8Rjh0fkf5za0tUeFyAwDchQpENW/cutting_bread.mp4", "width": 512, "height": 512, "n_frames": 40, "guidance_scale": 7.5, "diffusion_prompt": "slicing a piece of salmon", "inversion_prompt": "", "num_diffusion_steps": 50, "num_inversion_steps": 50, "negative_diffusion_prompt": "ugly, blurry, low res, unrealistic, unaesthetic" }, "logs": "Using seed: 4087\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:24, 1.96it/s]\n 4%|▍ | 2/50 [00:01<00:24, 1.96it/s]\n 6%|▌ | 3/50 [00:01<00:24, 1.96it/s]\n 8%|▊ | 4/50 [00:02<00:23, 1.96it/s]\n 10%|█ | 5/50 [00:02<00:22, 1.96it/s]\n 12%|█▏ | 6/50 [00:03<00:22, 1.96it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 1.96it/s]\n 16%|█▌ | 8/50 [00:04<00:21, 1.96it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 1.96it/s]\n 20%|██ | 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2.90it/s]\n 6%|▌ | 3/50 [00:01<00:19, 2.38it/s]\n 8%|▊ | 4/50 [00:01<00:20, 2.19it/s]\n 10%|█ | 5/50 [00:02<00:21, 2.10it/s]\n 12%|█▏ | 6/50 [00:02<00:21, 2.05it/s]\n 14%|█▍ | 7/50 [00:03<00:21, 2.02it/s]\n 16%|█▌ | 8/50 [00:03<00:20, 2.00it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 1.99it/s]\n 20%|██ | 10/50 [00:04<00:20, 1.98it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 1.97it/s]\n 24%|██▍ | 12/50 [00:05<00:19, 1.97it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 1.97it/s]\n 28%|██▊ | 14/50 [00:06<00:18, 1.96it/s]\n 30%|███ | 15/50 [00:07<00:17, 1.96it/s]\n 32%|███▏ | 16/50 [00:07<00:17, 1.96it/s]\n 34%|███▍ | 17/50 [00:08<00:16, 1.96it/s]\n 36%|███▌ | 18/50 [00:08<00:16, 1.96it/s]\n 38%|███▊ | 19/50 [00:09<00:15, 1.96it/s]\n 40%|████ | 20/50 [00:09<00:15, 1.96it/s]\n 42%|████▏ | 21/50 [00:10<00:14, 1.96it/s]\n 44%|████▍ | 22/50 [00:10<00:14, 1.96it/s]\n 46%|████▌ | 23/50 [00:11<00:13, 1.96it/s]\n 48%|████▊ | 24/50 [00:11<00:13, 1.96it/s]\n 50%|█████ | 25/50 [00:12<00:12, 1.96it/s]\n 52%|█████▏ | 26/50 [00:12<00:12, 1.96it/s]\n 54%|█████▍ | 27/50 [00:13<00:11, 1.96it/s]\n 56%|█████▌ | 28/50 [00:13<00:11, 1.96it/s]\n 58%|█████▊ | 29/50 [00:14<00:10, 1.96it/s]\n 60%|██████ | 30/50 [00:14<00:10, 1.96it/s]\n 62%|██████▏ | 31/50 [00:15<00:09, 1.96it/s]\n 64%|██████▍ | 32/50 [00:15<00:09, 1.96it/s]\n 66%|██████▌ | 33/50 [00:16<00:08, 1.96it/s]\n 68%|██████▊ | 34/50 [00:16<00:08, 1.96it/s]\n 70%|███████ | 35/50 [00:17<00:07, 1.96it/s]\n 72%|███████▏ | 36/50 [00:17<00:07, 1.96it/s]\n 74%|███████▍ | 37/50 [00:18<00:06, 1.96it/s]\n 76%|███████▌ | 38/50 [00:19<00:06, 1.96it/s]\n 78%|███████▊ | 39/50 [00:19<00:05, 1.96it/s]\n 80%|████████ | 40/50 [00:20<00:05, 1.96it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 1.96it/s]\n 84%|████████▍ | 42/50 [00:21<00:04, 1.96it/s]\n 86%|████████▌ | 43/50 [00:21<00:03, 1.96it/s]\n 88%|████████▊ | 44/50 [00:22<00:03, 1.96it/s]\n 90%|█████████ | 45/50 [00:22<00:02, 1.95it/s]\n 92%|█████████▏| 46/50 [00:23<00:02, 1.95it/s]\n 94%|█████████▍| 47/50 [00:23<00:01, 1.95it/s]\n 96%|█████████▌| 48/50 [00:24<00:01, 1.96it/s]\n 98%|█████████▊| 49/50 [00:24<00:00, 1.96it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.96it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.99it/s]\nInversion completed!\nNumber of frames for editing: 40\nSampling: 0%| | 0/50 [00:00<?, ?it/s]\nSampling: 2%|▏ | 1/50 [00:02<02:25, 2.97s/it]\nSampling: 4%|▍ | 2/50 [00:05<02:22, 2.97s/it]\nSampling: 6%|▌ | 3/50 [00:08<02:19, 2.97s/it]\nSampling: 8%|▊ | 4/50 [00:11<02:16, 2.97s/it]\nSampling: 10%|█ | 5/50 [00:14<02:13, 2.97s/it]\nSampling: 12%|█▏ | 6/50 [00:17<02:10, 2.97s/it]\nSampling: 14%|█▍ | 7/50 [00:20<02:07, 2.97s/it]\nSampling: 16%|█▌ | 8/50 [00:23<02:04, 2.98s/it]\nSampling: 18%|█▊ | 9/50 [00:26<02:01, 2.97s/it]\nSampling: 20%|██ | 10/50 [00:29<01:58, 2.97s/it]\nSampling: 22%|██▏ | 11/50 [00:32<01:56, 2.98s/it]\nSampling: 24%|██▍ | 12/50 [00:35<01:53, 2.98s/it]\nSampling: 26%|██▌ | 13/50 [00:38<01:50, 2.98s/it]\nSampling: 28%|██▊ | 14/50 [00:41<01:47, 2.98s/it]\nSampling: 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2.97s/it]\nSampling: 68%|██████▊ | 34/50 [01:41<00:47, 2.97s/it]\nSampling: 70%|███████ | 35/50 [01:44<00:44, 2.97s/it]\nSampling: 72%|███████▏ | 36/50 [01:47<00:41, 2.97s/it]\nSampling: 74%|███████▍ | 37/50 [01:50<00:38, 2.97s/it]\nSampling: 76%|███████▌ | 38/50 [01:53<00:35, 2.97s/it]\nSampling: 78%|███████▊ | 39/50 [01:56<00:32, 2.97s/it]\nSampling: 80%|████████ | 40/50 [01:58<00:29, 2.97s/it]\nSampling: 82%|████████▏ | 41/50 [02:01<00:26, 2.97s/it]\nSampling: 84%|████████▍ | 42/50 [02:04<00:23, 2.97s/it]\nSampling: 86%|████████▌ | 43/50 [02:07<00:20, 2.97s/it]\nSampling: 88%|████████▊ | 44/50 [02:10<00:17, 2.97s/it]\nSampling: 90%|█████████ | 45/50 [02:13<00:14, 2.97s/it]\nSampling: 92%|█████████▏| 46/50 [02:16<00:11, 2.97s/it]\nSampling: 94%|█████████▍| 47/50 [02:19<00:08, 2.97s/it]\nSampling: 96%|█████████▌| 48/50 [02:22<00:05, 2.97s/it]\nSampling: 98%|█████████▊| 49/50 [02:25<00:02, 2.98s/it]\nSampling: 100%|██████████| 50/50 [02:28<00:00, 2.97s/it]\nSampling: 100%|██████████| 50/50 [02:28<00:00, 2.97s/it]\nDone!", "metrics": { "predict_time": 220.685382, "total_time": 220.724014 }, "output": "https://replicate.delivery/pbxt/0x2oBe7gMZUlFaohT9pJhJl92ezpGuQOCmeGVAh1uyuzUteIB/out.mp4", "started_at": "2024-01-23T12:57:33.237444Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/btogko3bewjnkplzkbx2yjevz4", "cancel": "https://api.replicate.com/v1/predictions/btogko3bewjnkplzkbx2yjevz4/cancel" }, "version": "d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728" }
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