Instructions to use Tharwat-Elsayed/SpeachClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Tharwat-Elsayed/SpeachClassification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Tharwat-Elsayed/SpeachClassification") - Notebooks
- Google Colab
- Kaggle
Download Random_Forest_Model.pkl from Tharwat-Elsayed/SpeachClassification: direct link, hf CLI and curl.
- Browser
- Download file 93.3 kB
-
https://huggingface.co/Tharwat-Elsayed/SpeachClassification/resolve/main/Random_Forest_Model.pkl
- Command line
-
hf download hf://Tharwat-Elsayed/SpeachClassification/Random_Forest_Model.pkl
-
curl -L -o Random_Forest_Model.pkl https://huggingface.co/Tharwat-Elsayed/SpeachClassification/resolve/main/Random_Forest_Model.pkl
93.3 kB
- Xet hash:
- 5028f55052ebbef35e0fb667e9b44d968d68a9324cec061350bac4c70c6ad68a
- Size of remote file:
- 93.3 kB
- SHA256:
- c67a90939eeb7904db3ddde7c7909cacb1cce822f61a1248975628b1e1edf46f
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