Instructions to use Expendadeur/agro-bio-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Expendadeur/agro-bio-models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Expendadeur/agro-bio-models") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68258c1dded3d0ee49fbf8db3123ad40d7ddd271851590d2c5ea39610e3163d9
- Size of remote file:
- 933 MB
- SHA256:
- e0e7ea62aac136a944eb9df49251ed7045d389253e3d91166a08674010f06226
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.