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:
- 11a4de5b86efd764e0da406d1aa6bae16bff9ded68f070279ea2cc2b22983d17
- Size of remote file:
- 34.6 kB
- SHA256:
- 2339fa7dc93436351e9b091d1b1e2a41d8fe928a27ad3bd3c053ee301bfc9c17
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