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lion-ai
/
embeddinggemma-300m-medembed-triplets2

Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:230357
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use lion-ai/embeddinggemma-300m-medembed-triplets2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use lion-ai/embeddinggemma-300m-medembed-triplets2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("lion-ai/embeddinggemma-300m-medembed-triplets2")
    
    sentences = [
        "What were the results of the functional study using RNA and cDNA derivatives of the BRCA1 c.5074+3A>C variant?",
        "The patient was discharged on [date of discharge] and his most recent HbA1c level was 7.1% with a few episodes of hypoglycemia.",
        "The patient was diagnosed with stage IV NSCLC (malignant pleural effusion) in December 2014. Adenocarcinoma cells from pleural effusion were found, and immunohistochemistry analysis demonstrated positivity in TTF-1 and negativity in CK 5/6 and P63.",
        "Based on the results of the functional study using RNA and cDNA derivatives of the BRCA1 c.5074+3A>C variant, it is a likely pathogenic variant."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
embeddinggemma-300m-medembed-triplets2 / 3_Dense
9.44 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
AleksanderObuchowski's picture
AleksanderObuchowski
Add new SentenceTransformer model
8630bf8 verified 11 months ago
  • config.json
    134 Bytes
    Add new SentenceTransformer model 11 months ago
  • model.safetensors
    9.44 MB
    xet
    Add new SentenceTransformer model 11 months ago