// npm i @xenova/transformersimport { pipeline, cos_sim } from'@xenova/transformers';
// Create feature extraction pipelineconst extractor = awaitpipeline('feature-extraction', 'Xenova/jina-embeddings-v2-small-en',
{ quantized: false } // Comment out this line to use the quantized version
);
// Generate embeddingsconst output = awaitextractor(
['How is the weather today?', 'What is the current weather like today?'],
{ pooling: 'mean' }
);
// Compute cosine similarityconsole.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
and structuring your repo like this one (with ONNX weights located in a subfolder named
onnx
).
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