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roomnumber103
/
embedding-BOK

Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:10501
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use roomnumber103/embedding-BOK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use roomnumber103/embedding-BOK with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("roomnumber103/embedding-BOK")
    
    sentences = [
        "추운날이니 외출은 자제해주시기 바랍니다.",
        "추운날인데 외출하지마",
        "소·돼지에 대해서만 실시하던 축산물이력제가 1월 1일부터 닭·오리·계란까지 확대·시행된다.",
        "광고메일함 비중이 에어비앤비가 더 높니 트립닷컴이 더 많니?"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
embedding-BOK
444 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
roomnumber103's picture
roomnumber103
msg
7324130 almost 2 years ago
  • 1_Pooling
    msg almost 2 years ago
  • .DS_Store
    6.15 kB
    msg almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    15.1 kB
    msg almost 2 years ago
  • config.json
    776 Bytes
    msg almost 2 years ago
  • config_sentence_transformers.json
    201 Bytes
    msg almost 2 years ago
  • model.safetensors
    442 MB
    xet
    msg almost 2 years ago
  • modules.json
    229 Bytes
    msg almost 2 years ago
  • sentence_bert_config.json
    52 Bytes
    msg almost 2 years ago
  • special_tokens_map.json
    971 Bytes
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  • tokenizer.json
    752 kB
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  • tokenizer_config.json
    1.47 kB
    msg almost 2 years ago
  • vocab.txt
    248 kB
    msg almost 2 years ago