Instructions to use DaneshSelwal/Classification-DIAS-65Bands with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use DaneshSelwal/Classification-DIAS-65Bands 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://DaneshSelwal/Classification-DIAS-65Bands") - Notebooks
- Google Colab
- Kaggle
Download ensemble/models/AlexNet_CNN_final.keras from DaneshSelwal/Classification-DIAS-65Bands: direct link, hf CLI and curl.
- Browser
- Download file 273 MB
-
https://huggingface.co/DaneshSelwal/Classification-DIAS-65Bands/resolve/main/ensemble/models/AlexNet_CNN_final.keras
- Command line
-
hf download hf://DaneshSelwal/Classification-DIAS-65Bands/ensemble/models/AlexNet_CNN_final.keras
-
curl -L -o AlexNet_CNN_final.keras https://huggingface.co/DaneshSelwal/Classification-DIAS-65Bands/resolve/main/ensemble/models/AlexNet_CNN_final.keras
273 MB
- Xet hash:
- ab148bb3448a0a4b9064cc569ff27239d67e876ce0cbff32a6263c4c7b2b7733
- Size of remote file:
- 273 MB
- SHA256:
- de8a912c691bb541c15b3565d2e532f5d71e1c8ae308f8e32c0dc615afc88489
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