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kuljeet98
/
bert-model

Sentence Similarity
sentence-transformers
PyTorch
bert
feature-extraction
Generated from Trainer
dataset_size:8408
loss:CosineSimilarityLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use kuljeet98/bert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use kuljeet98/bert-model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("kuljeet98/bert-model")
    
    sentences = [
        "president",
        "assistante de banque priv e banco santander rio",
        "worldwide executive vice president corindus a siemens healthineers company",
        "soporte t cnico superior"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
bert-model
503 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
kuljeet98's picture
kuljeet98
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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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  • modules.json
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  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    471 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    1.42 kB
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  • unigram.json
    14.8 MB
    xet
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