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

Usage with πŸ€— Transformers.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-base-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));  // 0.9341313949712492 (unquantized) vs. 0.9022937687830741 (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 πŸ€— Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).

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