technillogue/cog-triton-webrtc:cae798cb | Run with an API on Replicate

Version

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technillogue /cog-triton-webrtc:cae798cb

Playground API

Input

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

npx create-replicate --model=technillogue/cog-triton-webrtc

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

const output = await replicate.run(
  "technillogue/cog-triton-webrtc:cae798cb91cdb3991ddcb65affcd615e0a8b5dc04c79e1b005fddb1e255e802e",
  {
    input: {
      top_k: 0,
      top_p: 0,
      temperature: 1,
      length_penalty: 1,
      max_new_tokens: 250,
      presence_penalty: 0
    }
  }
);

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

output = replicate.run(
    "technillogue/cog-triton-webrtc:cae798cb91cdb3991ddcb65affcd615e0a8b5dc04c79e1b005fddb1e255e802e",
    input={
        "top_k": 0,
        "top_p": 0,
        "temperature": 1,
        "length_penalty": 1,
        "max_new_tokens": 250,
        "presence_penalty": 0
    }
)

# The technillogue/cog-triton-webrtc 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/cog-triton-webrtc/api#output-schema
    print(item, end="")

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/cog-triton-webrtc 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/cog-triton-webrtc:cae798cb91cdb3991ddcb65affcd615e0a8b5dc04c79e1b005fddb1e255e802e",
    "input": {
      "top_k": 0,
      "top_p": 0,
      "temperature": 1,
      "length_penalty": 1,
      "max_new_tokens": 250,
      "presence_penalty": 0
    }
  }' \
  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/cog-triton-webrtc@sha256:cae798cb91cdb3991ddcb65affcd615e0a8b5dc04c79e1b005fddb1e255e802e \
  -i 'top_k=0' \
  -i 'top_p=0' \
  -i 'temperature=1' \
  -i 'length_penalty=1' \
  -i 'max_new_tokens=250' \
  -i 'presence_penalty=0'

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/technillogue/cog-triton-webrtc@sha256:cae798cb91cdb3991ddcb65affcd615e0a8b5dc04c79e1b005fddb1e255e802e
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "top_k": 0,
      "top_p": 0,
      "temperature": 1,
      "length_penalty": 1,
      "max_new_tokens": 250,
      "presence_penalty": 0
    }
  }' \
  http://localhost:5000/predictions

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

Output

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