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hoin1218
/
bge-m3-business-compact-card-context-v2

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:3210
loss:CosineSimilarityLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use hoin1218/bge-m3-business-compact-card-context-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use hoin1218/bge-m3-business-compact-card-context-v2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("hoin1218/bge-m3-business-compact-card-context-v2")
    
    sentences = [
        "말및양사육업사업체1 말 및 양 사육업 영업본부 고객사 방문 국내 평일",
        "콜센터및텔레마케팅서비스업사업체1 콜센터 및 텔레마케팅 서비스업 워크숍 준비 참석자 지원 비용",
        "광고영화및비디오물제작업사업체1 광고 영화 및 비디오물 제작업 영업본부 고객사 방문 국내 평일",
        "도장및기타피막처리업사업체1 도장 및 기타 피막처리업 재무팀 월말 결산 법인카드"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
bge-m3-business-compact-card-context-v2
2.29 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
hoin1218's picture
hoin1218
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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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  • 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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