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berg-embed
/
Qwen3_0.6B_RB_F1

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

Instructions to use berg-embed/Qwen3_0.6B_RB_F1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use berg-embed/Qwen3_0.6B_RB_F1 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("berg-embed/Qwen3_0.6B_RB_F1")
    
    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

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  • 1_Pooling
    Add new SentenceTransformer model 4 months ago
  • .gitattributes
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  • README.md
    3.83 kB
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  • added_tokens.json
    707 Bytes
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  • chat_template.jinja
    4.17 kB
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  • config.json
    1.35 kB
    Add new SentenceTransformer model 4 months ago
  • config_sentence_transformers.json
    283 Bytes
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  • merges.txt
    1.67 MB
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  • model.safetensors
    2.38 GB
    xet
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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
    613 Bytes
    Add new SentenceTransformer model 4 months ago
  • tokenizer.json
    11.4 MB
    xet
    Add new SentenceTransformer model 4 months ago
  • tokenizer_config.json
    5.43 kB
    Add new SentenceTransformer model 4 months ago
  • vocab.json
    2.78 MB
    Add new SentenceTransformer model 4 months ago