ductridev/animate-diff:c9fbe524 – Run with an API on Replicate

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ductridev /animate-diff:c9fbe524

Playground API

Input

model

string

Model to run. All model provide at civitai.com text-to-image models

Default: "ToonYou"

motion_model

string

Model to run. All model provide at civitai.com text-to-image models

Default: "Motion V14 Checkpoint"

additional_model

string

Additional model to combine with main model.

Default: "None"

init_image

file

Init image

prompt

string

Shift + Return to add a new line

The prompt or prompts to guide the video generation.

Default: "anime"

negative_prompt

string

Shift + Return to add a new line

The prompt or prompts not to guide the video generation.

Default: "noise, text, nude"

cfg_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance (minimum: 1; maximum: 20)

Default: 9

height

integer

(minimum: 512)

Height of the generated video

Default: 512

width

integer

(minimum: 512)

Width of the generated video

Default: 512

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps (minimum: 1; maximum: 500)

Default: 25

seed

integer

Random seed. Leave blank to randomize the seed

lora_alpha

number

(minimum: 0.1, maximum: 1)

scaling factor for the weight matrices

Default: 0.6

nums_frame

integer

(minimum: 8)

Number frames of video

Default: 16

fps

integer

fps for the output video

Default: 24

Run this model in Node.js with one line of code:

npx create-replicate --model=ductridev/animate-diff

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set 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 ductridev/animate-diff using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ductridev/animate-diff:c9fbe5243ecfd90d2460bed77b9333afa1d2689344b9cc1976c71fd0db529d23",
  {
    input: {
      fps: 24,
      model: "ToonYou",
      width: 512,
      height: 512,
      prompt: "anime",
      cfg_scale: 9,
      lora_alpha: 0.6,
      nums_frame: 16,
      motion_model: "Motion V14 Checkpoint",
      negative_prompt: "noise, text, nude",
      additional_model: "None",
      num_inference_steps: 25
    }
  }
);

// 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 replicate

Set 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 replicate

Run ductridev/animate-diff using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ductridev/animate-diff:c9fbe5243ecfd90d2460bed77b9333afa1d2689344b9cc1976c71fd0db529d23",
    input={
        "fps": 24,
        "model": "ToonYou",
        "width": 512,
        "height": 512,
        "prompt": "anime",
        "cfg_scale": 9,
        "lora_alpha": 0.6,
        "nums_frame": 16,
        "motion_model": "Motion V14 Checkpoint",
        "negative_prompt": "noise, text, nude",
        "additional_model": "None",
        "num_inference_steps": 25
    }
)
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 ductridev/animate-diff 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": "c9fbe5243ecfd90d2460bed77b9333afa1d2689344b9cc1976c71fd0db529d23",
    "input": {
      "fps": 24,
      "model": "ToonYou",
      "width": 512,
      "height": 512,
      "prompt": "anime",
      "cfg_scale": 9,
      "lora_alpha": 0.6,
      "nums_frame": 16,
      "motion_model": "Motion V14 Checkpoint",
      "negative_prompt": "noise, text, nude",
      "additional_model": "None",
      "num_inference_steps": 25
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/ductridev/animate-diff@sha256:c9fbe5243ecfd90d2460bed77b9333afa1d2689344b9cc1976c71fd0db529d23 \
  -i 'fps=24' \
  -i 'model="ToonYou"' \
  -i 'width=512' \
  -i 'height=512' \
  -i 'prompt="anime"' \
  -i 'cfg_scale=9' \
  -i 'lora_alpha=0.6' \
  -i 'nums_frame=16' \
  -i 'motion_model="Motion V14 Checkpoint"' \
  -i 'negative_prompt="noise, text, nude"' \
  -i 'additional_model="None"' \
  -i 'num_inference_steps=25'

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/ductridev/animate-diff@sha256:c9fbe5243ecfd90d2460bed77b9333afa1d2689344b9cc1976c71fd0db529d23
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "fps": 24,
      "model": "ToonYou",
      "width": 512,
      "height": 512,
      "prompt": "anime",
      "cfg_scale": 9,
      "lora_alpha": 0.6,
      "nums_frame": 16,
      "motion_model": "Motion V14 Checkpoint",
      "negative_prompt": "noise, text, nude",
      "additional_model": "None",
      "num_inference_steps": 25
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

No output yet! Press "Submit" to start a prediction.