https://huggingface.co/BAAI/bge-reranker-base with ONNX weights to be compatible with Transformers.js.
Usage (Transformers.js)
If you haven't already, you can install the Transformers.js JavaScript library from NPM using:
npm i @huggingface/transformers
Example: Text classification using a reranker model.
import { pipeline } from '@huggingface/transformers';
const classifier = await pipeline('text-classification', 'Xenova/bge-reranker-base');
const output = await classifier('I love transformers!');
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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BAAI/bge-reranker-base
from sentence_transformers import CrossEncoder model = CrossEncoder("Xenova/bge-reranker-base") query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores)