Instructions to use dilkushsingh/Facial_Emotion_Recognizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use dilkushsingh/Facial_Emotion_Recognizer 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://dilkushsingh/Facial_Emotion_Recognizer") - Notebooks
- Google Colab
- Kaggle
Download ResNet50_Transfer_Learning/saved_model.pb from dilkushsingh/Facial_Emotion_Recognizer: direct link, hf CLI and curl.
- Browser
- Download file 3.26 MB
-
https://huggingface.co/dilkushsingh/Facial_Emotion_Recognizer/resolve/main/ResNet50_Transfer_Learning/saved_model.pb
- Command line
-
hf download hf://dilkushsingh/Facial_Emotion_Recognizer/ResNet50_Transfer_Learning/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/dilkushsingh/Facial_Emotion_Recognizer/resolve/main/ResNet50_Transfer_Learning/saved_model.pb
3.26 MB
- Xet hash:
- 8f626c212631bcc0a7793adea458a267ac9244177037d52923c3b68676fdf65e
- Size of remote file:
- 3.26 MB
- SHA256:
- 7c293a85747bbd42b7c7eaa8b19e222bf4d13936742e0831cfca96b74c19645a
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