Instructions to use Heizsenberg/tomato-leaf-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Heizsenberg/tomato-leaf-classification with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Heizsenberg/tomato-leaf-classification") - Notebooks
- Google Colab
- Kaggle
Download metadata.json from Heizsenberg/tomato-leaf-classification: direct link, hf CLI and curl.
- Browser
- Download file 64 Bytes
-
https://huggingface.co/Heizsenberg/tomato-leaf-classification/resolve/main/metadata.json
- Command line
-
hf download hf://Heizsenberg/tomato-leaf-classification/metadata.json
-
curl -L -o metadata.json https://huggingface.co/Heizsenberg/tomato-leaf-classification/resolve/main/metadata.json
64 Bytes
| {"keras_version": "3.12.1", "date_saved": "2026-02-16@08:38:25"} |