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ng3owb
/
sentiment-embedding-model

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ng3owb/sentiment-embedding-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ng3owb/sentiment-embedding-model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ng3owb/sentiment-embedding-model")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
sentiment-embedding-model / 1_Pooling
3.27 kB
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  • 1 contributor
History: 1 commit
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ng3owb
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  • config (1).json
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  • config (10).json
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  • config (2).json
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  • config (5).json
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  • config (6).json
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  • config (7).json
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  • config (8).json
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  • config (9).json
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  • config.json
    297 Bytes
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