Versions
d456a26c
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You're looking at a specific version of this model. Jump to the model overview.
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=cjwbw/tokenflow
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_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 replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun 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 the
REPLICATE_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/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/chenxwh/tokenflow@sha256:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728 \
-i 'fps=20' \
-i 'video="https://replicate.delivery/pbxt/KGcnUKDlfys2uAo8eHbWSE8Pzc17hI5IOGdstViaBvfPJWHY/wolf.mp4"' \
-i 'width=512' \
-i 'height=512' \
-i 'n_frames=40' \
-i 'guidance_scale=7.5' \
-i 'diffusion_prompt="a shiny silver robotic wolf"' \
-i 'inversion_prompt=""' \
-i 'num_diffusion_steps=50' \
-i 'num_inversion_steps=50' \
-i 'negative_diffusion_prompt="ugly, blurry, low res, unrealistic, unaesthetic"'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/chenxwh/tokenflow@sha256:d456a26c0c1764ac4d9b933a564fe70e660c46423ba0afb5d3200f1a46060728curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "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" } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.27. Alternatively, try out our featured models for free.
Sign in with GitHub
By signing in, you agree to our
terms of service and privacy policy
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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[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 in
Using 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. Please use pts_unit 'sec'.")
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Inversion completed!
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Done!