charlesmccarthy/hallo:62721ac7 – Run with an API on Replicate

Version

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charlesmccarthy /hallo:62721ac7

Playground API

Input

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

npx create-replicate --model=charlesmccarthy/hallo

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 charlesmccarthy/hallo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "charlesmccarthy/hallo:62721ac79864834a3b1f58565d648253294a5a2b519193914b42e3f324f3743c",
  {
    input: {
      config: "config.yaml",
      output: "output.mp4",
      lip_weight: 0.5,
      face_weight: 0.5,
      pose_weight: 0.5,
      face_expand_ratio: 1
    }
  }
);

// 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 charlesmccarthy/hallo using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "charlesmccarthy/hallo:62721ac79864834a3b1f58565d648253294a5a2b519193914b42e3f324f3743c",
    input={
        "config": "config.yaml",
        "output": "output.mp4",
        "lip_weight": 0.5,
        "face_weight": 0.5,
        "pose_weight": 0.5,
        "face_expand_ratio": 1
    }
)
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 charlesmccarthy/hallo 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": "62721ac79864834a3b1f58565d648253294a5a2b519193914b42e3f324f3743c",
    "input": {
      "config": "config.yaml",
      "output": "output.mp4",
      "lip_weight": 0.5,
      "face_weight": 0.5,
      "pose_weight": 0.5,
      "face_expand_ratio": 1
    }
  }' \
  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/charlesmccarthy/hallo@sha256:62721ac79864834a3b1f58565d648253294a5a2b519193914b42e3f324f3743c \
  -i 'config="config.yaml"' \
  -i 'output="output.mp4"' \
  -i 'lip_weight=0.5' \
  -i 'face_weight=0.5' \
  -i 'pose_weight=0.5' \
  -i 'face_expand_ratio=1'

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/charlesmccarthy/hallo@sha256:62721ac79864834a3b1f58565d648253294a5a2b519193914b42e3f324f3743c
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "config": "config.yaml",
      "output": "output.mp4",
      "lip_weight": 0.5,
      "face_weight": 0.5,
      "pose_weight": 0.5,
      "face_expand_ratio": 1
    }
  }' \
  http://localhost:5000/predictions

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

Output

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