Instructions to use okeowo1014/trainingsample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use okeowo1014/trainingsample 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://okeowo1014/trainingsample") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from okeowo1014/trainingsample: direct link, hf CLI and curl.
- Browser
- Download file 188 kB
-
https://huggingface.co/okeowo1014/trainingsample/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://okeowo1014/trainingsample@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/okeowo1014/trainingsample/resolve/refs%2Fpr%2F1/saved_model.pb
188 kB
- Xet hash:
- 3c483903dfb662862ad1b1ed5ea105ba131aff735754cce60f50e48991c2ca9d
- Size of remote file:
- 188 kB
- SHA256:
- 524e63cd44af91c9d31bdde3d710240046e87f1940461f9c9c40ff7abc51bd98
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