nateraw/mpnet-base-v2-batched – Run with an API on Replicate

nateraw / mpnet-base-v2-batched

Cold

Public
24 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=nateraw/mpnet-base-v2-batched

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 nateraw/mpnet-base-v2-batched using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/mpnet-base-v2-batched:71fb56f019b5f86d7db64e6698245c6f5fcd9a06df1f7fca42c52b02bc97c2c0",
  {
    input: {
      texts: "",
      batch_size: 32,
      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 nateraw/mpnet-base-v2-batched using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/mpnet-base-v2-batched:71fb56f019b5f86d7db64e6698245c6f5fcd9a06df1f7fca42c52b02bc97c2c0",
    input={
        "texts": "",
        "batch_size": 32,
        "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 nateraw/mpnet-base-v2-batched 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": "71fb56f019b5f86d7db64e6698245c6f5fcd9a06df1f7fca42c52b02bc97c2c0",
    "input": {
      "texts": "",
      "batch_size": 32,
      "normalize_embeddings": true
    }
  }' \
  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/nateraw/mpnet-base-v2-batched@sha256:71fb56f019b5f86d7db64e6698245c6f5fcd9a06df1f7fca42c52b02bc97c2c0 \
  -i 'texts=""' \
  -i 'batch_size=32' \
  -i 'normalize_embeddings=true'

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/nateraw/mpnet-base-v2-batched@sha256:71fb56f019b5f86d7db64e6698245c6f5fcd9a06df1f7fca42c52b02bc97c2c0
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "texts": "",
      "batch_size": 32,
      "normalize_embeddings": true
    }
  }' \
  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 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.