yorickvp / jina-embeddings-v2-small-en

An English, monolingual embedding model supporting 8192 sequence length (33M version)

Cold

Public
33 runs
CPU
Paper
License

Run with an API

Playground API Examples README Versions

Prediction

yorickvp/jina-embeddings-v2-small-en:f15f8646

Model

yorickvp/jina-embeddings-v2-small-en:e4dcaeb8

6ksvu5jbncc5dy7gcivmwgxmj4

Status

Succeeded

Source

Web

Hardware

CPU

Total duration

24.1s

Created

over 1 year ago

Input

text: hello, world!
output_format: base64

{
  "text": "hello, world!",
  "output_format": "base64"
}

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 yorickvp/jina-embeddings-v2-small-en using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yorickvp/jina-embeddings-v2-small-en:f15f8646534dd26ec85585dfb25edbf6133bd30535eb77b2f9e6a078c419723b",
  {
    input: {
      text: "hello, world!",
      output_format: "base64"
    }
  }
);
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 yorickvp/jina-embeddings-v2-small-en using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yorickvp/jina-embeddings-v2-small-en:f15f8646534dd26ec85585dfb25edbf6133bd30535eb77b2f9e6a078c419723b",
    input={
        "text": "hello, world!",
        "output_format": "base64"
    }
)
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 yorickvp/jina-embeddings-v2-small-en 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": "f15f8646534dd26ec85585dfb25edbf6133bd30535eb77b2f9e6a078c419723b",
    "input": {
      "text": "hello, world!",
      "output_format": "base64"
    }
  }' \
  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/yorickvp/jina-embeddings-v2-small-en@sha256:f15f8646534dd26ec85585dfb25edbf6133bd30535eb77b2f9e6a078c419723b \
  -i 'text="hello, world!"' \
  -i 'output_format="base64"'

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/yorickvp/jina-embeddings-v2-small-en@sha256:f15f8646534dd26ec85585dfb25edbf6133bd30535eb77b2f9e6a078c419723b
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "text": "hello, world!",
      "output_format": "base64"
    }
  }' \
  http://localhost:5000/predictions

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

Output

text

hello, world!

vectors

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

{
  "completed_at": "2023-11-03T14:47:32.236756Z",
  "created_at": "2023-11-03T14:47:08.106916Z",
  "data_removed": false,
  "error": null,
  "id": "6ksvu5jbncc5dy7gcivmwgxmj4",
  "input": {
    "text": "hello, world!",
    "output_format": "base64"
  },
  "logs": null,
  "metrics": {
    "predict_time": 0.028873,
    "total_time": 24.12984
  },
  "output": [
    {
      "text": "hello, world!",
      "vectors": "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"
    }
  ],
  "started_at": "2023-11-03T14:47:32.207883Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/6ksvu5jbncc5dy7gcivmwgxmj4",
    "cancel": "https://api.replicate.com/v1/predictions/6ksvu5jbncc5dy7gcivmwgxmj4/cancel"
  },
  "version": "e4dcaeb8190cf7ce9e0353310a6774f039aaa7aacd597cf9624c75ad11e8f254"
}

Generated in

29 milliseconds

Tweak it Share Report

Want to make some of these yourself?

Run this model