anotherjesse/vid2vid-protototype – Run with an API on Replicate

anotherjesse / vid2vid-protototype

Cold

Public
178 runs
A100 (80GB)

Run with an API

Playground API Examples README Versions

Input

prompt

string

Shift + Return to add a new line

Input prompt

Default: "An astronaut riding a horse"

negative_prompt

string

Shift + Return to add a new line

Negative prompt

init_video

file

URL of the initial video (optional)

init_weight

number

Strength of init_video

Default: 0.5

num_frames

integer

Number of frames for the output video

Default: 24

num_inference_steps

integer

(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

width

integer

(minimum: 256)

Width of the output video

Default: 576

height

integer

(minimum: 256)

Height of the output video

Default: 320

guidance_scale

number

(minimum: 1, maximum: 100)

Guidance scale

Default: 7.5

fps

integer

fps for the output video

Default: 8

model

string

Model to use

Default: "xl"

batch_size

integer

(minimum: 1)

Batch size

Default: 1

remove_watermark

boolean

Remove watermark

Default: false

seed

integer

Random seed. Leave blank to randomize the seed

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

npx create-replicate --model=anotherjesse/vid2vid-protototype

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 anotherjesse/vid2vid-protototype using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "anotherjesse/vid2vid-protototype:e15715f57b6a6d8ea1aecd723fafae1208f948e37609e561863c2eae474fb4fb",
  {
    input: {
      fps: 8,
      model: "xl",
      width: 576,
      height: 320,
      prompt: "An astronaut riding a horse",
      batch_size: 1,
      num_frames: 24,
      init_weight: 0.5,
      guidance_scale: 7.5,
      remove_watermark: false,
      num_inference_steps: 50
    }
  }
);
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 anotherjesse/vid2vid-protototype using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "anotherjesse/vid2vid-protototype:e15715f57b6a6d8ea1aecd723fafae1208f948e37609e561863c2eae474fb4fb",
    input={
        "fps": 8,
        "model": "xl",
        "width": 576,
        "height": 320,
        "prompt": "An astronaut riding a horse",
        "batch_size": 1,
        "num_frames": 24,
        "init_weight": 0.5,
        "guidance_scale": 7.5,
        "remove_watermark": False,
        "num_inference_steps": 50
    }
)
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 anotherjesse/vid2vid-protototype 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": "e15715f57b6a6d8ea1aecd723fafae1208f948e37609e561863c2eae474fb4fb",
    "input": {
      "fps": 8,
      "model": "xl",
      "width": 576,
      "height": 320,
      "prompt": "An astronaut riding a horse",
      "batch_size": 1,
      "num_frames": 24,
      "init_weight": 0.5,
      "guidance_scale": 7.5,
      "remove_watermark": false,
      "num_inference_steps": 50
    }
  }' \
  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/anotherjesse/vid2vid-protototype@sha256:e15715f57b6a6d8ea1aecd723fafae1208f948e37609e561863c2eae474fb4fb \
  -i 'fps=8' \
  -i 'model="xl"' \
  -i 'width=576' \
  -i 'height=320' \
  -i 'prompt="An astronaut riding a horse"' \
  -i 'batch_size=1' \
  -i 'num_frames=24' \
  -i 'init_weight=0.5' \
  -i 'guidance_scale=7.5' \
  -i 'remove_watermark=false' \
  -i 'num_inference_steps=50'

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/anotherjesse/vid2vid-protototype@sha256:e15715f57b6a6d8ea1aecd723fafae1208f948e37609e561863c2eae474fb4fb
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "fps": 8,
      "model": "xl",
      "width": 576,
      "height": 320,
      "prompt": "An astronaut riding a horse",
      "batch_size": 1,
      "num_frames": 24,
      "init_weight": 0.5,
      "guidance_scale": 7.5,
      "remove_watermark": false,
      "num_inference_steps": 50
    }
  }' \
  http://localhost:5000/predictions

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

Output

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

Run time and cost

This model costs approximately $0.059 to run on Replicate, or 16 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 43 seconds. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.