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taide
/
embeddinggemma-GTAIDE-300m-2605

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

Instructions to use taide/embeddinggemma-GTAIDE-300m-2605 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use taide/embeddinggemma-GTAIDE-300m-2605 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("taide/embeddinggemma-GTAIDE-300m-2605")
    
    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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This repository is publicly accessible, but you have to accept the conditions to access its files and content.

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Preview of files found in this repository
  • 1_Pooling
    initial commit about 1 month ago
  • 2_Dense
    initial commit about 1 month ago
  • 3_Dense
    initial commit about 1 month ago
  • .gitattributes
    1.75 kB
    initial commit about 1 month ago
  • README.md
    14 kB
    Update README.md about 1 month ago
  • config.json
    1.64 kB
    initial commit about 1 month ago
  • config_sentence_transformers.json
    992 Bytes
    initial commit about 1 month ago
  • model.safetensors
    1.21 GB
    xet
    initial commit about 1 month ago
  • modules.json
    573 Bytes
    initial commit about 1 month ago
  • sentence_bert_config.json
    58 Bytes
    initial commit about 1 month ago
  • tokenizer.json
    33.4 MB
    xet
    initial commit about 1 month ago
  • tokenizer_config.json
    839 Bytes
    initial commit about 1 month ago