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vec-ai
/
lychee-embed

Sentence Similarity
sentence-transformers
Safetensors
Transformers
qwen2
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use vec-ai/lychee-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use vec-ai/lychee-embed with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("vec-ai/lychee-embed")
    
    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]
  • Transformers

    How to use vec-ai/lychee-embed with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("vec-ai/lychee-embed")
    model = AutoModel.from_pretrained("vec-ai/lychee-embed")
  • Notebooks
  • Google Colab
  • Kaggle
lychee-embed
3.09 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 9 commits
izhx's picture
izhx
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • chat_template.jinja
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  • config.json
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  • config_sentence_transformers.json
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  • framework-crop.png
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  • merges.txt
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  • model.safetensors
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  • modules.json
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  • special_tokens_map.json
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  • tokenizer_config.json
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  • vocab.json
    2.78 MB
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