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creative-graphic-design
/
MVANet

Feature Extraction
Transformers
Safetensors
mvanet
custom_code
Model card Files Files and versions
xet
Community

Instructions to use creative-graphic-design/MVANet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use creative-graphic-design/MVANet with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="creative-graphic-design/MVANet", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("creative-graphic-design/MVANet", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
MVANet
381 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
shunk031's picture
shunk031
Upload processor
f685c19 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    5.17 kB
    Upload MVANetForImageSegmentation 4 months ago
  • config.json
    788 Bytes
    Upload MVANetForImageSegmentation 4 months ago
  • configuration_mvanet.py
    4.73 kB
    Upload MVANetForImageSegmentation 4 months ago
  • image_processing_mvanet.py
    9.32 kB
    Upload processor 4 months ago
  • model.safetensors
    381 MB
    xet
    Upload MVANetForImageSegmentation 4 months ago
  • modeling_mvanet.py
    49.1 kB
    Upload MVANetForImageSegmentation 4 months ago
  • preprocessor_config.json
    373 Bytes
    Upload processor 4 months ago