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KMH158
/
vit_base_neurofusion_classification

Image Classification
Transformers
Safetensors
vit
Model card Files Files and versions
xet
Community

Instructions to use KMH158/vit_base_neurofusion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use KMH158/vit_base_neurofusion_classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="KMH158/vit_base_neurofusion_classification")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForImageClassification
    
    processor = AutoImageProcessor.from_pretrained("KMH158/vit_base_neurofusion_classification")
    model = AutoModelForImageClassification.from_pretrained("KMH158/vit_base_neurofusion_classification")
  • Notebooks
  • Google Colab
  • Kaggle
vit_base_neurofusion_classification
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  • 1 contributor
History: 3 commits
KMH158's picture
KMH158
Upload feature extractor
23c6ebd verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.17 kB
    Upload ViTForImageClassification about 1 year ago
  • config.json
    1.34 kB
    Upload ViTForImageClassification about 1 year ago
  • model.safetensors
    343 MB
    xet
    Upload ViTForImageClassification about 1 year ago
  • preprocessor_config.json
    353 Bytes
    Upload feature extractor about 1 year ago