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avsolatorio
/
GIST-Embedding-v0

Sentence Similarity
sentence-transformers
PyTorch
Safetensors
English
bert
feature-extraction
mteb
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
3

Instructions to use avsolatorio/GIST-Embedding-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use avsolatorio/GIST-Embedding-v0 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("avsolatorio/GIST-Embedding-v0")
    
    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]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
GIST-Embedding-v0
Ctrl+K
Ctrl+K
  • 2 contributors
History: 6 commits
tomaarsen's picture
tomaarsen HF Staff
Specify library_name metadata
5e8fd84 verified over 2 years ago
  • 1_Pooling
    Upload model to Hf Hub over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    116 kB
    Specify library_name metadata over 2 years ago
  • commit-info.json
    230 Bytes
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  • config.json
    747 Bytes
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  • config_sentence_transformers.json
    124 Bytes
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  • model.safetensors
    438 MB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    52 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    711 kB
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  • tokenizer_config.json
    1.24 kB
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  • vocab.txt
    232 kB
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