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databio
/
sbert-encode-cellines-tuned

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:1128
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use databio/sbert-encode-cellines-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use databio/sbert-encode-cellines-tuned with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("databio/sbert-encode-cellines-tuned")
    
    sentences = [
        "connective tissue cell",
        "GM18507",
        "GM18526",
        "GM08714"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
sbert-encode-cellines-tuned
1.52 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
ClaudeHu05's picture
ClaudeHu05
initial commit
c35d465 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago