Instructions to use IshanKumar/molecular_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use IshanKumar/molecular_generation with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://IshanKumar/molecular_generation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50515f6b8cd857bc28c93be59e2525c36f8344adf53750f8470e68fc5d622af7
- Size of remote file:
- 1.5 kB
- SHA256:
- 572f5957cfbbf7f6a495153a0dd9cfc0255a40a88df7b74b3ddc82d8889b3660
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