Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Which Approach is recommended for Fine-Tuning Molecular Property Prediction #216

Open
ASIWU opened this issue Apr 18, 2024 · 1 comment
Open

Comments

@ASIWU
Copy link

ASIWU commented Apr 18, 2024

I am working on fine-tuning uni-mol for predicting molecular properties and have noticed an inconsistency in the data processing methods provided in the repository. There are some small differences between the smi2_3Dcoords function in the example notebook and the inner_smi2coords function in the conformer.py file within the MolTrain class for unimol_tools.

So, which approach is more recommended for fine-tuning unimol for molecular property prediction — example jupyter notebook or the MolTrain in unimol_tools ?

Best regards,

@Naplessss
Copy link
Contributor

smi2_3dcoords is for conformation diversity for docking initial, we prefer to use inner_smi2coords as just use MMFF force sampling coordinates for fientuning.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants