Addition of trained model checkpoint files (or torchscript) to the repo about mace

[ilyes319]

Hey, thank you for your issue.
Could you make the problem more precise? After training, the model is saved as .model in your folder, and you can easily load it in the ASE caclulator afterwards (see the calculator documentation.)

[kryczko]

Sure, I can make my request more precise. The models that we're used to produce the results in this paper: https://arxiv.org/pdf/2305.14247.pdf. Could the checkpoints for them be uploaded here and used in the following way:

from mace.models import MaceOrganic

model = MaceOrganic() # reads in checkpoint file
calc = model.ase() # convert to ASE calculator

energy = calc.get_potential_energy()

An example of this can be seen in torchani: https://aiqm.github.io/torchani/api.html#module-torchani.models

This would make it very easy for me to do my own benchmarking.

I hope this is more clear.

[davkovacs]

Checkpoints are here, we have uploaded them:
https://mace-docs.readthedocs.io/en/latest/examples/training_examples.html#ani-1x-dataset-h-c-n-o-transferable-ff
And the ASE calculator example is here:
https://mace-docs.readthedocs.io/en/latest/guide/ase.html

[kryczko]

Cool thanks, is this the correct link: https://github.com/ACEsuit/mace/blob/docs/docs/examples/ANI_trained_MACE.zip?

It still would be easier if these files were just stored on github and we could just define a class rather than downloading a zip and loading those files into a class.

[davkovacs]

That is the correct link.

Thank you for the recommendation. I will consider it once we release our own organic force field based on MACE. For now this checkpoint is meant for people who just want to try a MACE trained on ANI dataset, but this is not a thoroughly tested and benchmarked model, so I would not want to include it in the repo.