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newmindai
/
modernbert-base-tr-uncased-allnli-stsb

Sentence Similarity
sentence-transformers
Safetensors
Turkish
modernbert
feature-extraction
Generated from Trainer
dataset_size:482091
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
dataset_size:5749
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use newmindai/modernbert-base-tr-uncased-allnli-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use newmindai/modernbert-base-tr-uncased-allnli-stsb with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("newmindai/modernbert-base-tr-uncased-allnli-stsb")
    
    sentences = [
        "Ya da dışarı çıkıp yürü ya da biraz koşun. Bunu düzenli olarak yapmıyorum ama Washington bunu yapmak için harika bir yer.",
        "“Washington's yürüyüş ya da koşu için harika bir yer.”",
        "H-2A uzaylılar Amerika Birleşik Devletleri'nde zaman kısa süreleri var.",
        "“Washington'da düzenli olarak yürüyüşe ya da koşuya çıkıyorum.”"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
modernbert-base-tr-uncased-allnli-stsb
540 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
ozayezerceli's picture
ozayezerceli
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e146f25 verified about 1 year ago
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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
    540 MB
    xet
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  • modules.json
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  • sentence_bert_config.json
    53 Bytes
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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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