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jonc
/
my-embedding-gemma

Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:3
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use jonc/my-embedding-gemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use jonc/my-embedding-gemma with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("jonc/my-embedding-gemma")
    
    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]
  • Notebooks
  • Google Colab
  • Kaggle
my-embedding-gemma / 3_Dense
9.44 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
jonc's picture
jonc
Add new SentenceTransformer model
de902d0 verified 8 months ago
  • config.json
    134 Bytes
    Add new SentenceTransformer model 8 months ago
  • model.safetensors
    9.44 MB
    xet
    Add new SentenceTransformer model 8 months ago