technillogue/concurrent-hello:8098eb66 | Run with an API on Replicate

Version

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technillogue /concurrent-hello:8098eb66

Playground API

Input

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

npx create-replicate --model=technillogue/concurrent-hello

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

const output = await replicate.run(
  "technillogue/concurrent-hello:8098eb66a85002a7b8a3a9b430733bbbfb9aeda7c71b50234a079a87c566c095",
  {
    input: {
      n: 100,
      log: true,
      name: "",
      sleep: 0.0001,
      name_file: ""
    }
  }
);

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

output = replicate.run(
    "technillogue/concurrent-hello:8098eb66a85002a7b8a3a9b430733bbbfb9aeda7c71b50234a079a87c566c095",
    input={
        "n": 100,
        "log": True,
        "name": "",
        "sleep": 0.0001,
        "name_file": ""
    }
)

# The technillogue/concurrent-hello 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/technillogue/concurrent-hello/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 technillogue/concurrent-hello 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": "technillogue/concurrent-hello:8098eb66a85002a7b8a3a9b430733bbbfb9aeda7c71b50234a079a87c566c095",
    "input": {
      "n": 100,
      "log": true,
      "name": "",
      "sleep": 0.0001,
      "name_file": ""
    }
  }' \
  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/technillogue/concurrent-hello@sha256:8098eb66a85002a7b8a3a9b430733bbbfb9aeda7c71b50234a079a87c566c095 \
  -i 'n=100' \
  -i 'log=true' \
  -i 'name=""' \
  -i 'sleep=0.0001' \
  -i 'name_file=""'

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/technillogue/concurrent-hello@sha256:8098eb66a85002a7b8a3a9b430733bbbfb9aeda7c71b50234a079a87c566c095
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "n": 100,
      "log": true,
      "name": "",
      "sleep": 0.0001,
      "name_file": ""
    }
  }' \
  http://localhost:5000/predictions

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

Output

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