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efederici
/
sentence-it5-base

Sentence Similarity
sentence-transformers
PyTorch
Transformers
Italian
t5
feature-extraction
Model card Files Files and versions
xet
Community
1

Instructions to use efederici/sentence-it5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use efederici/sentence-it5-base with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("efederici/sentence-it5-base")
    
    sentences = [
        "Questa è una persona felice",
        "Questo è un cane felice",
        "Questa è una persona molto felice",
        "Oggi è una giornata di sole"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Transformers

    How to use efederici/sentence-it5-base with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("efederici/sentence-it5-base")
    model = AutoModel.from_pretrained("efederici/sentence-it5-base")
  • Notebooks
  • Google Colab
  • Kaggle
sentence-it5-base
441 MB
Ctrl+K
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  • 1 contributor
History: 6 commits
efederici's picture
efederici
Update model
73d3d9a about 4 years ago
  • 1_Pooling
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  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • README.md
    3.07 kB
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  • config.json
    697 Bytes
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  • config_sentence_transformers.json
    124 Bytes
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  • modules.json
    229 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    438 MB
    xet
    Update model about 4 years ago
  • sentence_bert_config.json
    54 Bytes
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  • special_tokens_map.json
    1.79 kB
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  • tokenizer.json
    2.05 MB
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  • tokenizer_config.json
    1.92 kB
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