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alpecevit
/
gte-multilingual-base-turkish

Sentence Similarity
sentence-transformers
Safetensors
new
custom_code
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use alpecevit/gte-multilingual-base-turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use alpecevit/gte-multilingual-base-turkish with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("alpecevit/gte-multilingual-base-turkish", trust_remote_code=True)
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
gte-multilingual-base-turkish
1.24 GB
Ctrl+K
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  • 1 contributor
History: 4 commits
alpecevit's picture
alpecevit
Update README.md
770b3e4 verified 11 months ago
  • 1_Pooling
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  • .gitattributes
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  • README.md
    1.56 kB
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  • config.json
    1.47 kB
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  • config_sentence_transformers.json
    277 Bytes
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  • configuration.py
    7.13 kB
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  • model.safetensors
    1.22 GB
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  • modeling.py
    59 kB
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    58 Bytes
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  • special_tokens_map.json
    964 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    1.37 kB
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