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HugC
/
VisME-Qwen25VL-7B

Feature Extraction
Transformers
Safetensors
qwen2_5_vl
image-text-to-text
embedding
multimodal
vision-language
mmeb
mveb
Model card Files Files and versions
xet
Community
1

Instructions to use HugC/VisME-Qwen25VL-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use HugC/VisME-Qwen25VL-7B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="HugC/VisME-Qwen25VL-7B")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForMultimodalLM
    
    processor = AutoProcessor.from_pretrained("HugC/VisME-Qwen25VL-7B")
    model = AutoModelForMultimodalLM.from_pretrained("HugC/VisME-Qwen25VL-7B", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
VisME-Qwen25VL-7B / assets
423 kB
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  • 1 contributor
History: 1 commit
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HugC
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  • performance.jpg
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  • teaser.jpg
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