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Xenova
/
bge-reranker-large

Text Ranking
Transformers.js
ONNX
sentence-transformers
xlm-roberta
text-classification
text-embeddings-inference
Model card Files Files and versions
xet
Community
4

Instructions to use Xenova/bge-reranker-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers.js

    How to use Xenova/bge-reranker-large with Transformers.js:

    // npm i @huggingface/transformers
    import { pipeline } from '@huggingface/transformers';
    
    // Allocate pipeline
    const pipe = await pipeline('text-ranking', 'Xenova/bge-reranker-large');
  • sentence-transformers

    How to use Xenova/bge-reranker-large with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Xenova/bge-reranker-large")
    
    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)
  • Notebooks
  • Google Colab
  • Kaggle
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  • Hub documentation

change max_position_embeddings to be compatible with cpu + optimum

2
#1 opened over 1 year ago by
ishootlaser
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