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KYUNGHYUN9
/
test_model

Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:574417
loss:MultipleNegativesRankingLoss
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use KYUNGHYUN9/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use KYUNGHYUN9/test_model with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("KYUNGHYUN9/test_model")
    
    sentences = [
        "파타키는 아브라함의 결정을 칭찬했고 리파 회장 리차드 케셀은 케이블이 영구적으로 가동되어야 한다고 말했다.",
        "이스라엘과 하마스 '일시적인 휴전을 받아들이다'",
        "리파 회장 리차드 케셀은 \"우리가 보기에 케이블이 사용될 수 있다\"고 말했다.",
        "하지만 그들은 그들의 유권자들에게 책임이 있다."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
test_model
444 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
KYUNGHYUN9's picture
KYUNGHYUN9
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  • 1_Pooling
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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
    442 MB
    xet
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  • modules.json
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  • sentence_bert_config.json
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  • similarity_evaluation_sts-test_results.csv
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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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  • vocab.txt
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