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GRAI-UNSTPB
/
multilingual-e5-small-RoD-TAL

Sentence Similarity
sentence-transformers
Safetensors
Romanian
bert
information-retrieval
legal
romanian
rag
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use GRAI-UNSTPB/multilingual-e5-small-RoD-TAL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use GRAI-UNSTPB/multilingual-e5-small-RoD-TAL with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("GRAI-UNSTPB/multilingual-e5-small-RoD-TAL")
    
    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]
  • Notebooks
  • Google Colab
  • Kaggle

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  • 1_Pooling
    Add new SentenceTransformer model 4 months ago
  • .gitattributes
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  • OLD_README.md
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  • README.md
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    Update organization name in documentation after migration 20 days ago
  • config.json
    622 Bytes
    Add new SentenceTransformer model 4 months ago
  • config_sentence_transformers.json
    277 Bytes
    Add new SentenceTransformer model 4 months ago
  • model.safetensors
    471 MB
    xet
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  • modules.json
    349 Bytes
    Add new SentenceTransformer model 4 months ago
  • sentence_bert_config.json
    57 Bytes
    Add new SentenceTransformer model 4 months ago
  • special_tokens_map.json
    965 Bytes
    Add new SentenceTransformer model 4 months ago
  • tokenizer.json
    17.1 MB
    xet
    Add new SentenceTransformer model 4 months ago
  • tokenizer_config.json
    1.39 kB
    Add new SentenceTransformer model 4 months ago