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ssmits
/
Falcon2-5.5B-multilingual-embed-base

Text Classification
sentence-transformers
Safetensors
falcon
ssmits/Falcon2-5.5B-multilingual
custom_code
Model card Files Files and versions
xet
Community

Instructions to use ssmits/Falcon2-5.5B-multilingual-embed-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ssmits/Falcon2-5.5B-multilingual-embed-base with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("ssmits/Falcon2-5.5B-multilingual-embed-base", trust_remote_code=True)
    
    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
Falcon2-5.5B-multilingual-embed-base
10.4 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 17 commits
ssmits's picture
ssmits
Update README.md
cda5b4c verified about 2 years ago
  • 1_Pooling
    Upload 1_Pooling_config.json about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    3.87 kB
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  • config.json
    1.4 kB
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  • generation_config.json
    118 Bytes
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  • model-00001-of-00003.safetensors
    4.98 GB
    xet
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  • model-00002-of-00003.safetensors
    4.93 GB
    xet
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  • model-00003-of-00003.safetensors
    487 MB
    xet
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  • model.safetensors.index.json
    14.8 kB
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  • special_tokens_map.json
    676 Bytes
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  • tokenizer.json
    2.73 MB
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  • tokenizer_config.json
    3.3 kB
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