mattt/concurrent-hello-world | Run with an API on Replicate

Input

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

npx create-replicate --model=mattt/concurrent-hello-world

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 mattt/concurrent-hello-world using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "mattt/concurrent-hello-world:5c8736a5115cc50e63e1d760e4217075142372728e3f771bd4ebc6c47f8926da",
  {
    input: {
      name: "World"
    }
  }
);

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 mattt/concurrent-hello-world using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "mattt/concurrent-hello-world:5c8736a5115cc50e63e1d760e4217075142372728e3f771bd4ebc6c47f8926da",
    input={
        "name": "World"
    }
)

# The mattt/concurrent-hello-world model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/mattt/concurrent-hello-world/api#output-schema
    print(item)

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 mattt/concurrent-hello-world 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": "mattt/concurrent-hello-world:5c8736a5115cc50e63e1d760e4217075142372728e3f771bd4ebc6c47f8926da",
    "input": {
      "name": "World"
    }
  }' \
  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/mattt/concurrent-hello-world@sha256:5c8736a5115cc50e63e1d760e4217075142372728e3f771bd4ebc6c47f8926da \
  -i 'name="World"'

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 r8.im/mattt/concurrent-hello-world@sha256:5c8736a5115cc50e63e1d760e4217075142372728e3f771bd4ebc6c47f8926da
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "name": "World"
    }
  }' \
  http://localhost:5000/predictions

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

Output

hello World (#9)

Generated in

11.0 seconds

Tweak it Report View full prediction

This output was created using a different version of the model, mattt/concurrent-hello-world:b496bea9.

Run time and cost

This model runs on CPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.