| ### Tutorials | |
| As part of the [NeurIPS 2021 Climate Change AI Workshop](https://www.climatechange.ai/papers/neurips2021/79), a comprehensive, interactive Google-Colab tutorial notebook can be found [here](https://colab.research.google.com/github/Open-Catalyst-Project/ocp/blob/master/tutorials/OCP_Tutorial.ipynb). This notebook is designed for those new to OC20 and interested in how to get started. Topics include: | |
| * Background | |
| * Software Requirements | |
| * Dataset overview & Visualization | |
| * OCP Tasks - Train, Validate, Predict | |
| * IS2RE | |
| * S2EF | |
| * IS2RS | |
| * OCP Calculator | |
| * Model Development | |
| Additionally, we provide several Jupyter notebooks: | |
| * [Data preprocessing](https://github.com/Open-Catalyst-Project/ocp/blob/master/tutorials/data_preprocessing.ipynb) - preprocessing raw ASE atoms object to OCP graph Data objects. | |
| * [LMDB dataset creation](https://github.com/Open-Catalyst-Project/ocp/blob/master/tutorials/lmdb_dataset_creation.ipynb) - creating your own OCP-comatible LMDB datasets from ASE-compatible Atoms objects. | |
| * [Data visualization](https://github.com/Open-Catalyst-Project/ocp/blob/master/tutorials/data_visualization.ipynb) - understanding the raw data and its contents. (same contents found in the above google colab notebook) | |
| * [S2EF training example](https://github.com/Open-Catalyst-Project/ocp/blob/master/tutorials/train_s2ef_example.ipynb) - training a SchNet S2EF model, loading a trained model, and making predictions. (same contents found in the above google colab notebook). | |