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afiyarah
/
gemma-ins-make

Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:33973
loss:CosineSimilarityLoss
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use afiyarah/gemma-ins-make with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use afiyarah/gemma-ins-make with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("afiyarah/gemma-ins-make")
    
    sentences = [
        "In the car insurance domain, represent this car make entity in arabic for entity similarity matching: يو دي",
        "In the car insurance domain, represent this car make entity in arabic and english for entity similarity matching: ppm",
        "In the car insurance domain, represent this car make entity in arabic for entity similarity matching: إس دي إل جي",
        "In the car insurance domain, represent this car make entity in arabic for entity similarity matching: كارد نر"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
gemma-ins-make / eval
284 Bytes
Ctrl+K
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  • 1 contributor
History: 1 commit
afiyarah's picture
afiyarah
Upload fine-tuned insurance entity matching model
d2a842c verified 9 months ago
  • similarity_evaluation_insurance-val_results.csv
    284 Bytes
    Upload fine-tuned insurance entity matching model 9 months ago