LiteRT
Keras
English
tensorflow
emotion-recognition
transformer
lstm
mediapipe
computer-vision
deep-learning
facial-expression
affective-computing
sequential-data
Eval Results (legacy)
Instructions to use PSewmuthu/EmotionFormer-BiLSTM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use PSewmuthu/EmotionFormer-BiLSTM 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://PSewmuthu/EmotionFormer-BiLSTM") - Notebooks
- Google Colab
- Kaggle
Download images/Confusion_Matrix.png from PSewmuthu/EmotionFormer-BiLSTM: direct link, hf CLI and curl.
- Browser
- Download file 34.3 kB
-
https://huggingface.co/PSewmuthu/EmotionFormer-BiLSTM/resolve/main/images/Confusion_Matrix.png
- Command line
-
hf download hf://PSewmuthu/EmotionFormer-BiLSTM/images/Confusion_Matrix.png
-
curl -L -o Confusion_Matrix.png https://huggingface.co/PSewmuthu/EmotionFormer-BiLSTM/resolve/main/images/Confusion_Matrix.png
34.3 kB

- Xet hash:
- a321d5b7aab0efac58ffbe3c874977be5f8bcc2595c5d81df6c0b5b11c20e13c
- Size of remote file:
- 34.3 kB
- SHA256:
- b696b6bfe4d9d96ad14684642e2cf18660e0814e8f651a9f7c6170ad22b15021
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