Instructions to use emresvd/u203 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use emresvd/u203 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://emresvd/u203") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from emresvd/u203: direct link, hf CLI and curl.
- Browser
- Download file 746 kB
-
https://huggingface.co/emresvd/u203/resolve/main/saved_model.pb
- Command line
-
hf download hf://emresvd/u203/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/emresvd/u203/resolve/main/saved_model.pb
746 kB
- Xet hash:
- 69a6e5682d202402c29036bd81104aff65d0155842e141ea2dda242e99f80ba4
- Size of remote file:
- 746 kB
- SHA256:
- f0dd41d981237cad8cfe4245977ea613be1f0c005ece918442e6810b60db679f
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