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NirSharon
/
sentiment

Text Classification
sentence-transformers
Safetensors
setfit
mpnet
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use NirSharon/sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use NirSharon/sentiment with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("NirSharon/sentiment")
    
    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]
  • setfit

    How to use NirSharon/sentiment with setfit:

    from setfit import SetFitModel
    
    model = SetFitModel.from_pretrained("NirSharon/sentiment")
  • Notebooks
  • Google Colab
  • Kaggle

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  • 1_Pooling
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
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  • model_head.pkl

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    • "sklearn.linear_model._logistic.LogisticRegression"

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    324 Bytes
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  • modules.json
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  • sentence_bert_config.json
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  • vocab.txt
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