Instructions to use AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei 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://AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei: direct link, hf CLI and curl.
- Browser
- Download file 1.25 MB
-
https://huggingface.co/AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei/resolve/main/saved_model.pb
- Command line
-
hf download hf://AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/AndreiUrsu/EmotionClasificationCVRepoUrsuAndrei/resolve/main/saved_model.pb
1.25 MB
- Xet hash:
- f95733b14e900c69ef56278fa955fb5a1eaf2a8afd0484174a4e6b58b768cbc7
- Size of remote file:
- 1.25 MB
- SHA256:
- 3c75a0a185eed4bc7f101ad400e55e05599bb5e836ea9727e54329f8ca64175f
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