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
| 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 |