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aamohame
/
hack_ai_embbedding_model

Sentence Similarity
sentence-transformers
Safetensors
English
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:80
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use aamohame/hack_ai_embbedding_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use aamohame/hack_ai_embbedding_model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("aamohame/hack_ai_embbedding_model")
    
    sentences = [
        "A man with blond-hair, and a brown shirt drinking out of a public water fountain.",
        "A blond man wearing a brown shirt is reading a book on a bench in the park",
        "The people are standing still on the curb.",
        "An elderly man sits in a small shop."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
hack_ai_embbedding_model / eval
93 Bytes
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
aamohame's picture
aamohame
Training in progress, step 10
a064587 verified about 17 hours ago
  • similarity_evaluation_pair-score-evaluator-dev_results.csv
    93 Bytes
    Training in progress, step 10 about 17 hours ago