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:
- 5f93a7bfe1d90ef377c7223ed71b3dd336cf83c9f4233ff1968cdc490a2cf67e
- Size of remote file:
- 2.33 kB
- SHA256:
- 54b020a38f62461bd85fa34491c6a9cd0bc411b6caec3f00363fc432e96a40ea
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