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KAUSTAcademy
/
RecipeMatching_Reference_Qwen3-Embedding-0.6B

Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
mathematics
retrieval
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use KAUSTAcademy/RecipeMatching_Reference_Qwen3-Embedding-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use KAUSTAcademy/RecipeMatching_Reference_Qwen3-Embedding-0.6B with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("KAUSTAcademy/RecipeMatching_Reference_Qwen3-Embedding-0.6B")
    
    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
RecipeMatching_Reference_Qwen3-Embedding-0.6B
1.2 GB
Ctrl+K
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  • 1 contributor
History: 3 commits
ALLIA12's picture
ALLIA12
Update README.md
9520aa5 verified 8 days ago
  • 1_Pooling
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  • .gitattributes
    1.57 kB
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  • README.md
    2.51 kB
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  • chat_template.jinja
    4.12 kB
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  • config.json
    1.41 kB
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  • config_sentence_transformers.json
    376 Bytes
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  • model.safetensors
    1.19 GB
    xet
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  • modules.json
    429 Bytes
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  • run_config.json
    3.72 kB
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
    377 Bytes
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