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
| pipeline_tag: image-classification | |
| tags: | |
| - pytorch_model_hub_mixin | |
| - model_hub_mixin | |
| This model has been pushed to the Hub using ****: | |
| - Repo: [More Information Needed] | |
| - Docs: [More Information Needed] |