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syang687
/
FinSentenceBERT

Sentence Similarity
sentence-transformers
Safetensors
Transformers
mpnet
feature-extraction
active-learning
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use syang687/FinSentenceBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use syang687/FinSentenceBERT with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("syang687/FinSentenceBERT")
    
    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]
  • Transformers

    How to use syang687/FinSentenceBERT with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("syang687/FinSentenceBERT")
    model = AutoModel.from_pretrained("syang687/FinSentenceBERT")
  • Notebooks
  • Google Colab
  • Kaggle
FinSentenceBERT
440 MB
Ctrl+K
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  • 1 contributor
History: 15 commits
syang687's picture
syang687
Update README.md
65787b8 verified almost 2 years ago
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  • .gitattributes
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  • config.json
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  • config_sentence_transformers.json
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  • model.safetensors
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  • modules.json
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  • sentence_bert_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • trainSTS_SBERT_AL.tsv
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  • vocab.txt
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