Image Classification
Keras
LiteRT
Spanish
agriculture
plant-disease
soybean
computer-vision
tensorflow-lite
edge-ai
Instructions to use alejandroramirezucb/glycine-vision-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use alejandroramirezucb/glycine-vision-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://alejandroramirezucb/glycine-vision-models") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
67de368 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:f7865b02ecff28edce8608ac97ecaea5d221d5040ee921ec868dd84e45b91e02
size 63337591
|