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yahyaabd
/
indosbert-bps-custom-tokenizer

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use yahyaabd/indosbert-bps-custom-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use yahyaabd/indosbert-bps-custom-tokenizer with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("yahyaabd/indosbert-bps-custom-tokenizer")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
indosbert-bps-custom-tokenizer
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  • 1 contributor
History: 3 commits
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yahyaabd
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  • .gitattributes
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  • README.md
    3.71 kB
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  • added_tokens.json
    1.67 kB
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  • config.json
    1.05 kB
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  • config_sentence_transformers.json
    205 Bytes
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  • model.safetensors
    1.34 GB
    xet
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  • modules.json
    229 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    726 kB
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  • tokenizer_config.json
    17.7 kB
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  • vocab.txt
    229 kB
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