Instructions to use NathanSegers/masterclass-2025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use NathanSegers/masterclass-2025 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://NathanSegers/masterclass-2025") - Notebooks
- Google Colab
- Kaggle
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Download README.md from NathanSegers/masterclass-2025: direct link, hf CLI and curl.
- Browser
- Download file 424 Bytes
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https://huggingface.co/NathanSegers/masterclass-2025/resolve/main/README.md
- Command line
-
hf download hf://NathanSegers/masterclass-2025/README.md
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curl -L -o README.md https://huggingface.co/NathanSegers/masterclass-2025/resolve/main/README.md
424 Bytes
metadata
library_name: keras
This model has been uploaded using the Keras library and can be used with JAX, TensorFlow, and PyTorch backends.
This model card has been generated automatically and should be completed by the model author. See Model Cards documentation for more information.
For more details about the model architecture, check out config.json.