Instructions to use TGrote11/Math_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TGrote11/Math_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TGrote11/Math_Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import CNN model = CNN.from_pretrained("TGrote11/Math_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from TGrote11/Math_Classification: direct link, hf CLI and curl.
- Browser
- Download file 126 Bytes
-
https://huggingface.co/TGrote11/Math_Classification/resolve/main/config.json
- Command line
-
hf download hf://TGrote11/Math_Classification/config.json
-
curl -L -o config.json https://huggingface.co/TGrote11/Math_Classification/resolve/main/config.json
126 Bytes
| { | |
| "architectures": [ | |
| "CNN" | |
| ], | |
| "model_type": "cnn", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.17.0" | |
| } | |