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Duplicated from  maidalun1020/bce-reranker-base_v1

nitsuai
/
bce-reranker-base_v1

Text Classification
sentence-transformers
PyTorch
Transformers
xlm-roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use nitsuai/bce-reranker-base_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use nitsuai/bce-reranker-base_v1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("nitsuai/bce-reranker-base_v1")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • Transformers

    How to use nitsuai/bce-reranker-base_v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="nitsuai/bce-reranker-base_v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("nitsuai/bce-reranker-base_v1")
    model = AutoModelForSequenceClassification.from_pretrained("nitsuai/bce-reranker-base_v1")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#2 opened 12 months ago by
SFconvertbot

Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`

#1 opened about 1 year ago by
tomaarsen
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