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TGrote11
/
Handwriting_Math_Classification

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

Instructions to use TGrote11/Handwriting_Math_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use TGrote11/Handwriting_Math_Classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="TGrote11/Handwriting_Math_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("TGrote11/Handwriting_Math_Classification")
    model = AutoModelForImageClassification.from_pretrained("TGrote11/Handwriting_Math_Classification")
  • Notebooks
  • Google Colab
  • Kaggle
Handwriting_Math_Classification
350 MB
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  • 1 contributor
History: 19 commits
TGrote11's picture
TGrote11
Upload feature extractor
146f2f9 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    211 Bytes
    Upload ResNetForImageClassification almost 2 years ago
  • config.json
    615 Bytes
    Upload ViTForImageClassification over 1 year ago
  • model.safetensors
    350 MB
    xet
    Upload ViTForImageClassification over 1 year ago
  • preprocessor_config.json
    327 Bytes
    Upload feature extractor over 1 year ago