dsingal0/mpnet-for-scale – Run with an API on Replicate

dsingal0 / mpnet-for-scale

Cold

Public
9 runs
T4

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=dsingal0/mpnet-for-scale

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 dsingal0/mpnet-for-scale using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "dsingal0/mpnet-for-scale:33dd982a2aa6ae1b76b02786aab397a285d7c2f1b923e899aa09c6db4506ca60",
  {
    input: {
      batch_size: 192,
      normalize_embeddings: true
    }
  }
);
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 dsingal0/mpnet-for-scale using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "dsingal0/mpnet-for-scale:33dd982a2aa6ae1b76b02786aab397a285d7c2f1b923e899aa09c6db4506ca60",
    input={
        "batch_size": 192,
        "normalize_embeddings": True
    }
)
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 dsingal0/mpnet-for-scale 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": "33dd982a2aa6ae1b76b02786aab397a285d7c2f1b923e899aa09c6db4506ca60",
    "input": {
      "batch_size": 192,
      "normalize_embeddings": true
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run dsingal0/mpnet-for-scale using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/dsingal0/mpnet-for-scale@sha256:33dd982a2aa6ae1b76b02786aab397a285d7c2f1b923e899aa09c6db4506ca60 \
  -i 'batch_size=192' \
  -i 'normalize_embeddings=true'

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

Pull and run dsingal0/mpnet-for-scale using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/dsingal0/mpnet-for-scale@sha256:33dd982a2aa6ae1b76b02786aab397a285d7c2f1b923e899aa09c6db4506ca60
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "batch_size": 192,
      "normalize_embeddings": true
    }
  }' \
  http://localhost:5000/predictions

Output

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

Run time and cost

This model runs on Nvidia T4 GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.