Instructions to use keras-io/MPNN-for-molecular-property-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/MPNN-for-molecular-property-prediction with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-io/MPNN-for-molecular-property-prediction") - Notebooks
- Google Colab
- Kaggle
Download keras_metadata.pb from keras-io/MPNN-for-molecular-property-prediction: direct link, hf CLI and curl.
- Browser
- Download file 25.1 kB
-
https://huggingface.co/keras-io/MPNN-for-molecular-property-prediction/resolve/main/keras_metadata.pb
- Command line
-
hf download hf://keras-io/MPNN-for-molecular-property-prediction/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/keras-io/MPNN-for-molecular-property-prediction/resolve/main/keras_metadata.pb
25.1 kB
- Xet hash:
- fa6d5adb06921702460feca5206ca982331afb3a6f4b5b1073784defc1a4cab9
- Size of remote file:
- 25.1 kB
- SHA256:
- cc37dccc2dd569564f8ad129b1d04d15c89f486bca499a0b17af566aee541c69
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