charlesmccarthy/wtest – Run with an API on Replicate

charlesmccarthy / wtest

Cold

Public
9 runs
L40S

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=charlesmccarthy/wtest

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

const output = await replicate.run(
  "charlesmccarthy/wtest:d87a3d99e6df127847fa71c2eb9bd3478b1173d60424284ca0249932eada0774",
  {
    input: {
      seed: -1,
      prompt: "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage.",
      sample_shift: 8,
      sample_steps: 50,
      frames_per_second: 16,
      sample_guide_scale: 6
    }
  }
);
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 charlesmccarthy/wtest using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "charlesmccarthy/wtest:d87a3d99e6df127847fa71c2eb9bd3478b1173d60424284ca0249932eada0774",
    input={
        "seed": -1,
        "prompt": "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage.",
        "sample_shift": 8,
        "sample_steps": 50,
        "frames_per_second": 16,
        "sample_guide_scale": 6
    }
)
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/wtest 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": "d87a3d99e6df127847fa71c2eb9bd3478b1173d60424284ca0249932eada0774",
    "input": {
      "seed": -1,
      "prompt": "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage.",
      "sample_shift": 8,
      "sample_steps": 50,
      "frames_per_second": 16,
      "sample_guide_scale": 6
    }
  }' \
  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/wtest@sha256:d87a3d99e6df127847fa71c2eb9bd3478b1173d60424284ca0249932eada0774 \
  -i 'seed=-1' \
  -i 'prompt="Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage."' \
  -i 'sample_shift=8' \
  -i 'sample_steps=50' \
  -i 'frames_per_second=16' \
  -i 'sample_guide_scale=6'

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/wtest@sha256:d87a3d99e6df127847fa71c2eb9bd3478b1173d60424284ca0249932eada0774
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": -1,
      "prompt": "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage.",
      "sample_shift": 8,
      "sample_steps": 50,
      "frames_per_second": 16,
      "sample_guide_scale": 6
    }
  }' \
  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 runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.