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eilph
/
turkish_math_embedding_alibaba

Sentence Similarity
sentence-transformers
Safetensors
new
feature-extraction
dense
Generated from Trainer
dataset_size:948
loss:ContrastiveTensionLoss
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use eilph/turkish_math_embedding_alibaba with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("eilph/turkish_math_embedding_alibaba", trust_remote_code=True)
    
    sentences = [
        "Yandaki şekilde A₁, A₂, A₃, ..., Aₙ noktaları çokgenin köşeleri; [A₁A₂], [A₂A₃], ..., [AₙA₁] çokgenin kenarlarıdır.",
        "Alıştırma özeti: Rasyonel ifadelerle yapılan bir bölme işleminin en sade sonucu bulunmaktadır.",
        "Alıştırma özeti: Faktöriyel içeren kesirli bir ifadenin değerini bulma alıştırması.",
        "Alıştırma özeti: Verilen doğrusal ve rasyonel fonksiyonların terslerinin kurallarının bulunması istenmektedir."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
turkish_math_embedding_alibaba
1.24 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
eilph's picture
eilph
Upload 11 files
d5b3ff3 verified 7 months ago
  • .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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  • configuration.py
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  • model.safetensors
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  • modeling.py
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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
    17.1 MB
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  • tokenizer_config.json
    1.18 kB
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