Instructions to use atuml/FishNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use atuml/FishNet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://atuml/FishNet") - Notebooks
- Google Colab
- Kaggle
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bfc33ff | 1 2 3 4 5 6 7 8 9 10 | 0 : Bacterial Red disease 1 : Bacterial diseases - Aeromoniasis 2 : Bacterial gill disease 3 : Fungal diseases Saprolegniasis 4 : Healthy Fish 5 : Parasitic diseases 6 : Viral diseases White tail disease Resource link: https://www.kaggle.com/code/ahmadjaved097/multiclass-image-classification-using-cnn |