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
- Xet hash:
- 1cd62cb248e926f92a32e8f68a1cb7ff37df2ad5a75810cf2d6e287c674aa154
- Size of remote file:
- 350 MB
- SHA256:
- b6f2d99e1cc6319b09f4b651b17ee63e570c40465a4a6d0e0c19256b8dd4fe11
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