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beclab
/
embeddinggemma-300m-ov

Feature Extraction
sentence-transformers
Safetensors
OpenVINO
English
multilingual
gemma3_text
sentence-similarity
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use beclab/embeddinggemma-300m-ov with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use beclab/embeddinggemma-300m-ov with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("beclab/embeddinggemma-300m-ov")
    
    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
embeddinggemma-300m-ov / 2_Dense
9.44 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
wangzhong's picture
wangzhong
Upload EmbeddingGemma-300M OpenVINO FP32 IR for IREmbeddingServer
45cf669 verified about 1 month ago
  • config.json
    134 Bytes
    Upload EmbeddingGemma-300M OpenVINO FP32 IR for IREmbeddingServer about 1 month ago
  • model.safetensors
    9.44 MB
    xet
    Upload EmbeddingGemma-300M OpenVINO FP32 IR for IREmbeddingServer about 1 month ago