Instructions to use CaptainHaaz/FERmodelCNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use CaptainHaaz/FERmodelCNN 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://CaptainHaaz/FERmodelCNN") - Notebooks
- Google Colab
- Kaggle
Download variables/variables.data-00000-of-00001 from CaptainHaaz/FERmodelCNN: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/CaptainHaaz/FERmodelCNN/resolve/6a575622f2bd5f63a0ce28be0e85481f6596b23f/variables/variables.data-00000-of-00001
- Command line
-
hf download hf://CaptainHaaz/FERmodelCNN@6a575622f2bd5f63a0ce28be0e85481f6596b23f/variables/variables.data-00000-of-00001
-
curl -L -o variables.data-00000-of-00001 https://huggingface.co/CaptainHaaz/FERmodelCNN/resolve/6a575622f2bd5f63a0ce28be0e85481f6596b23f/variables/variables.data-00000-of-00001
17.1 MB
- Xet hash:
- cddc27b3a31f047c7a867d2b3d4cc88c6f78e84992a77c7daa29d5a043270a42
- Size of remote file:
- 17.1 MB
- SHA256:
- a4683182f0a1ba203bff091a31451fee5138dcbb2346a0fc90d723445560e837
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