zsxkib/v-express:f3400fd3 – Run with an API on Replicate

Version

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zsxkib /v-express:f3400fd3

Playground API

Input

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

npx create-replicate --model=zsxkib/v-express

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 zsxkib/v-express using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zsxkib/v-express:f3400fd305d761778fea70c22b8951356187d4096ab5fc1a553d1333095cf7c6",
  {
    input: {
      retarget_strategy: "fix_face",
      num_inference_steps: 25,
      audio_attention_weight: 3,
      reference_attention_weight: 0.95
    }
  }
);
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 zsxkib/v-express using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zsxkib/v-express:f3400fd305d761778fea70c22b8951356187d4096ab5fc1a553d1333095cf7c6",
    input={
        "retarget_strategy": "fix_face",
        "num_inference_steps": 25,
        "audio_attention_weight": 3,
        "reference_attention_weight": 0.95
    }
)
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 zsxkib/v-express 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": "f3400fd305d761778fea70c22b8951356187d4096ab5fc1a553d1333095cf7c6",
    "input": {
      "retarget_strategy": "fix_face",
      "num_inference_steps": 25,
      "audio_attention_weight": 3,
      "reference_attention_weight": 0.95
    }
  }' \
  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/zsxkib/v-express@sha256:f3400fd305d761778fea70c22b8951356187d4096ab5fc1a553d1333095cf7c6 \
  -i 'retarget_strategy="fix_face"' \
  -i 'num_inference_steps=25' \
  -i 'audio_attention_weight=3' \
  -i 'reference_attention_weight=0.95'

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/zsxkib/v-express@sha256:f3400fd305d761778fea70c22b8951356187d4096ab5fc1a553d1333095cf7c6
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "retarget_strategy": "fix_face",
      "num_inference_steps": 25,
      "audio_attention_weight": 3,
      "reference_attention_weight": 0.95
    }
  }' \
  http://localhost:5000/predictions

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

Output

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