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Duplicated from  Qwen/Qwen3-VL-Reranker-2B

ArchiveStudio
/
Qwen3-VL-Reranker-2B

Text Ranking
Transformers
Safetensors
sentence-transformers
qwen3_vl
image-text-to-text
multimodal rerank
text rerank
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use ArchiveStudio/Qwen3-VL-Reranker-2B with Transformers:

    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("ArchiveStudio/Qwen3-VL-Reranker-2B")
    model = AutoModelForMultimodalLM.from_pretrained("ArchiveStudio/Qwen3-VL-Reranker-2B", device_map="auto")
  • sentence-transformers

    How to use ArchiveStudio/Qwen3-VL-Reranker-2B with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("ArchiveStudio/Qwen3-VL-Reranker-2B")
    
    query = "Which planet is known as the Red Planet?"
    passages = [
    	"Venus is often called Earth's twin because of its similar size and proximity.",
    	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
    	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
    	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
    ]
    
    scores = model.predict([(query, passage) for passage in passages])
    print(scores)
  • Notebooks
  • Google Colab
  • Kaggle
Qwen3-VL-Reranker-2B / scripts
10.9 kB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 1 commit
ArchiveStudio's picture
ArchiveStudio
littlebird13's picture
littlebird13
Duplicate from Qwen/Qwen3-VL-Reranker-2B
d4e7562 about 1 month ago
  • qwen3_vl_reranker.py
    10.9 kB
    Duplicate from Qwen/Qwen3-VL-Reranker-2B about 1 month ago