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Qwen
/
Qwen3-VL-Embedding-2B

Sentence Similarity
sentence-transformers
Safetensors
Transformers
qwen3_vl
image-text-to-text
multimodal embedding
qwen
embedding
Model card Files Files and versions
xet
Community
24

Instructions to use Qwen/Qwen3-VL-Embedding-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Qwen/Qwen3-VL-Embedding-2B with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Qwen/Qwen3-VL-Embedding-2B")
    
    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]
  • Transformers

    How to use Qwen/Qwen3-VL-Embedding-2B with Transformers:

    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-Embedding-2B")
    model = AutoModelForMultimodalLM.from_pretrained("Qwen/Qwen3-VL-Embedding-2B", device_map="auto")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
Qwen3-VL-Embedding-2B
4.27 GB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 5 commits
thenlper's picture
thenlper
update blog link
d0531a7 verified 8 months ago
  • scripts
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  • .gitattributes
    1.57 kB
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  • README.md
    13.1 kB
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  • added_tokens.json
    707 Bytes
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  • chat_template.jinja
    5.52 kB
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  • config.json
    1.57 kB
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  • merges.txt
    1.67 MB
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  • model.safetensors
    4.26 GB
    xet
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  • preprocessor_config.json
    783 Bytes
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    11.4 MB
    xet
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  • tokenizer_config.json
    5.4 kB
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  • video_preprocessor_config.json
    817 Bytes
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  • vocab.json
    2.78 MB
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