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usnistgov · Jun 1, 2024 · 91799e6 · 91799e6
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 | [Regression model](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/alignn_jarvis_leaderboard.ipynb)                                                       | [![Open in Google Colab]](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/alignn_jarvis_leaderboard.ipynb)                                 | Examples for developing single output regression model for exfoliation energies of 2D materials.                                                                                                                                                                                                                                                                       |
 | [MLFF](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_ALIGNNFF_Mlearn.ipynb)                                                  | [![Open in Google Colab]](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Train_ALIGNNFF_Mlearn.ipynb)                            | Examples of training a machine learning force field for Silicon.                                                                                                                                                                                                                                                                                                                                 |
-| [Miscellaneous tasks](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Training_ALIGNN_model_example.ipynb)                   | [![Open in Google Colab]](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Training_ALIGNN_model_example.ipynb)  | Examples for developing single output (such as formation energy, bandgaps) or multi-output (such as phonon DOS, electron DOS) Regression or Classification (such as metal vs non-metal), sing several pretrained models. |
+| [Miscellaneous tasks](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Training_ALIGNN_model_example.ipynb)                   | [![Open in Google Colab]](https://colab.research.google.com/github/knc6/jarvis-tools-notebooks/blob/master/jarvis-tools-notebooks/Training_ALIGNN_model_example.ipynb)  | Examples for developing single output (such as formation energy, bandgaps) or multi-output (such as phonon DOS, electron DOS) Regression or Classification (such as metal vs non-metal), Using several pretrained models. |
 
 
 [Open in Google Colab]: https://colab.research.google.com/assets/colab-badge.svg