README.md

---
base_model: jinaai/jina-embeddings-v2-small-en
library_name: transformers.js
pipeline_tag: feature-extraction
---

https://huggingface.co/jinaai/jina-embeddings-v2-small-en with ONNX weights to be compatible with Transformers.js.

## Usage with 🤗 Transformers.js

```js
// npm i @xenova/transformers
import { pipeline, cos_sim } from '@xenova/transformers';

// Create feature extraction pipeline
const extractor = await pipeline('feature-extraction', 'Xenova/jina-embeddings-v2-small-en',
    { quantized: false } // Comment out this line to use the quantized version
);

// Generate embeddings
const output = await extractor(
    ['How is the weather today?', 'What is the current weather like today?'],
    { pooling: 'mean' }
);

// Compute cosine similarity
console.log(cos_sim(output[0].data, output[1].data));  // 0.9399812684139274 (unquantized) vs. 0.9341121503699659 (quantized)
```

Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).