Instructions to use maia2000/mobilenet-food-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use maia2000/mobilenet-food-binary with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://maia2000/mobilenet-food-binary") - Notebooks
- Google Colab
- Kaggle
Binary Healthy/Unhealthy Food Classifier -- MobileNetV3Small
Frozen MobileNetV3Small + sigmoid head. Best val accuracy: 0.9118.
- unhealthy: burgers, candy_sweets, desserts, fried_food, pizza, salty_snacks, sugary_drinks
- healthy: fruits, grain_bowls, grilled_meat, salads, seafood, smoothies, soups, vegetables
- dataset: maia2000/food-classifier-dataset
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