andreasjansson/stable-diffusion-animation:abe37e64

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andreasjansson /stable-diffusion-animation:abe37e64

Playground API

Input

prompt_start

*string

Shift + Return to add a new line

Prompt to start the animation with

prompt_end

*string

Shift + Return to add a new line

Prompt to end the animation with

width

integer

Width of output image

Default: 512

height

integer

Height of output image

Default: 512

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

prompt_strength

number

Lower prompt strength generates more coherent gifs, higher respects prompts more but can be jumpy

Default: 0.8

num_animation_frames

integer

(minimum: 2, maximum: 50)

Number of frames to animate

Default: 10

num_interpolation_steps

integer

(minimum: 1, maximum: 50)

Number of steps to interpolate between animation frames

Default: 5

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

gif_frames_per_second

integer

(minimum: 1, maximum: 50)

Frames/second in output GIF

Default: 20

gif_ping_pong

boolean

Whether to reverse the animation and go back to the beginning before looping

Default: false

film_interpolation

boolean

Whether to use FILM for between-frame interpolation (film-net.github.io)

Default: false

seed

integer

Random seed. Leave blank to randomize the seed

output_format

string

Output file format

Default: "gif"

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

npx create-replicate --model=andreasjansson/stable-diffusion-animation

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 andreasjansson/stable-diffusion-animation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/stable-diffusion-animation:abe37e641fef457c21f21ca0d48394544c3527e19686a8c0ab89c2d1190e65c4",
  {
    input: {
      width: 512,
      height: 512,
      gif_ping_pong: false,
      output_format: "gif",
      guidance_scale: 7.5,
      prompt_strength: 0.8,
      film_interpolation: false,
      num_inference_steps: 50,
      num_animation_frames: 10,
      gif_frames_per_second: 20,
      num_interpolation_steps: 5
    }
  }
);
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 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 andreasjansson/stable-diffusion-animation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/stable-diffusion-animation:abe37e641fef457c21f21ca0d48394544c3527e19686a8c0ab89c2d1190e65c4",
    input={
        "width": 512,
        "height": 512,
        "gif_ping_pong": False,
        "output_format": "gif",
        "guidance_scale": 7.5,
        "prompt_strength": 0.8,
        "film_interpolation": False,
        "num_inference_steps": 50,
        "num_animation_frames": 10,
        "gif_frames_per_second": 20,
        "num_interpolation_steps": 5
    }
)
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 andreasjansson/stable-diffusion-animation 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": "abe37e641fef457c21f21ca0d48394544c3527e19686a8c0ab89c2d1190e65c4",
    "input": {
      "width": 512,
      "height": 512,
      "gif_ping_pong": false,
      "output_format": "gif",
      "guidance_scale": 7.5,
      "prompt_strength": 0.8,
      "film_interpolation": false,
      "num_inference_steps": 50,
      "num_animation_frames": 10,
      "gif_frames_per_second": 20,
      "num_interpolation_steps": 5
    }
  }' \
  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/andreasjansson/stable-diffusion-animation@sha256:abe37e641fef457c21f21ca0d48394544c3527e19686a8c0ab89c2d1190e65c4 \
  -i 'width=512' \
  -i 'height=512' \
  -i 'gif_ping_pong=false' \
  -i 'output_format="gif"' \
  -i 'guidance_scale=7.5' \
  -i 'prompt_strength=0.8' \
  -i 'film_interpolation=false' \
  -i 'num_inference_steps=50' \
  -i 'num_animation_frames=10' \
  -i 'gif_frames_per_second=20' \
  -i 'num_interpolation_steps=5'

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/andreasjansson/stable-diffusion-animation@sha256:abe37e641fef457c21f21ca0d48394544c3527e19686a8c0ab89c2d1190e65c4
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "width": 512,
      "height": 512,
      "gif_ping_pong": false,
      "output_format": "gif",
      "guidance_scale": 7.5,
      "prompt_strength": 0.8,
      "film_interpolation": false,
      "num_inference_steps": 50,
      "num_animation_frames": 10,
      "gif_frames_per_second": 20,
      "num_interpolation_steps": 5
    }
  }' \
  http://localhost:5000/predictions

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

Output

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