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tencent
/
R3-embedding-0.6b

Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
agent-skill-retrieval
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use tencent/R3-embedding-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use tencent/R3-embedding-0.6b with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("tencent/R3-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
R3-embedding-0.6b
2.39 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 6 commits
Tom Aarsen
Expand code snippet for easier use
3e15313 about 21 hours ago
  • 1_Pooling
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  • .gitattributes
    1.57 kB
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  • README.md
    1.83 kB
    Expand code snippet for easier use about 21 hours ago
  • chat_template.jinja
    4.12 kB
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  • config.json
    1.35 kB
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  • config_sentence_transformers.json
    364 Bytes
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  • model.safetensors
    2.38 GB
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    5.4 kB
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