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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- config.json +1 -1
- model.safetensors +2 -2
config.json
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