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_Model.h5 from dilkushsingh/Facial_Emotion_Recognizer: direct link, hf CLI and curl.
- Browser
- Download file 120 MB
-
https://huggingface.co/dilkushsingh/Facial_Emotion_Recognizer/resolve/main/ResNet50_Model.h5
- Command line
-
hf download hf://dilkushsingh/Facial_Emotion_Recognizer/ResNet50_Model.h5
-
curl -L -o ResNet50_Model.h5 https://huggingface.co/dilkushsingh/Facial_Emotion_Recognizer/resolve/main/ResNet50_Model.h5
120 MB
- Xet hash:
- 4f5566a73f7639d64056b957a349420f308a48e6af07b0d699c8bdf4211055c5
- Size of remote file:
- 120 MB
- SHA256:
- 378b85298a09c9829296c2f2fce43185c617248968941bede6c371f8d27b1806
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