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am-azadi
/
bilingual-embedding-large_Fine_Tuned_3e

Sentence Similarity
sentence-transformers
Safetensors
bilingual
feature-extraction
Generated from Trainer
dataset_size:21769
loss:MultipleNegativesRankingLoss
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use am-azadi/bilingual-embedding-large_Fine_Tuned_3e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use am-azadi/bilingual-embedding-large_Fine_Tuned_3e with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("am-azadi/bilingual-embedding-large_Fine_Tuned_3e", trust_remote_code=True)
    
    sentences = [
        "Amen.. This Quran was found at the bottom of the sea Has become a rock but still intact subhanallah, hopefully those who like it, comment amen and share this post sincerely the sustenance tomorrow morning will be abundant from the opposite direction unexpected.amen  اهيه",
        "Mexico deserves an Oscar for the coffin dance The video of uniformed men doing \"the coffin dance\" was recorded in Colombia, not in Mexico",
        "The Koran was found at the bottom of the sea already turned into a rock but still intact This is a dictionary covered in crystal and is a work of art by an American artist",
        "Video purported to be a video celebrating the inauguration of Hamas' new office in the Indian state of Kerala False, this claim is a video celebrating the inauguration of the Hamas office in India"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
bilingual-embedding-large_Fine_Tuned_3e
2.26 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
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  • config.py
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  • modules.json
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  • sentence_bert_config.json
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