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mjaliz
/
bslm-pair-original-multipositive

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:2991559
loss:CachedMultiPositiveRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use mjaliz/bslm-pair-original-multipositive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use mjaliz/bslm-pair-original-multipositive with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("mjaliz/bslm-pair-original-multipositive")
    
    sentences = [
        "کوله پشتی صندوقی پسرانه",
        "q-d6abe050cc50d858b466b2cb",
        "کوله پشتی صندوقی پسرانه طرح فضانورد وارداتی",
        "p-26697244",
        "کوله‌پشتی صندوقی پسرانه طرح فضانورد مدل وارداتی رنگ سرمه‌ای"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [5, 5]
  • Notebooks
  • Google Colab
  • Kaggle
bslm-pair-original-multipositive
2.29 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
mjaliz's picture
mjaliz
Upload best checkpoint (step 16000)
a81326d verified 7 days ago
  • 1_Pooling
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  • .gitattributes
    1.57 kB
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  • README.md
    76.7 kB
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  • config.json
    745 Bytes
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  • config_sentence_transformers.json
    284 Bytes
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  • model.safetensors
    2.27 GB
    xet
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  • modules.json
    277 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    573 Bytes
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  • training_args.bin
    5.52 kB
    xet
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