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MossaabDev
/
quran_embed_V2

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:193
loss:CosineSimilarityLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use MossaabDev/quran_embed_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use MossaabDev/quran_embed_V2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("MossaabDev/quran_embed_V2")
    
    sentences = [
        "I saw someone killing a cat in the street, I felt helpless and sad",
        "There is no god ?worthy of worship? except You. Glory be to You! I have certainly done wrong.",
        "who say, when struck by a disaster,  Surely to Allah we belong and to Him we will ?all? return. ",
        "And never think that Allah is unaware of what the wrongdoers do. He only delays them for a Day when eyes will stare [in horror]"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
quran_embed_V2
503 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
MossaabDev's picture
MossaabDev
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  • .gitattributes
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  • README.md
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
    471 MB
    xet
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  • modules.json
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  • sentence_bert_config.json
    60 Bytes
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  • special_tokens_map.json
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    1.51 kB
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  • unigram.json
    14.8 MB
    xet
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  • vocab.txt
    232 kB
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