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:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://atuml/FishNet") - Notebooks
- Google Colab
- Kaggle
File size: 303 Bytes
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 |