hard to fetch pre-trained unet from git lfs

[MilesZhao]

I tried to fetch the pre-trained unet and failed. Here is my steps. I have bought one pack from GitHub with 50 G a month.

git clone git@github.com:by256/icsg3d.git
cd icsg3d
git lfs install
git lfs track ".h5"
git lfs track ".hdf5"
git lfs fetch origin master

Error:
fetch: Fetching reference refs/heads/master
batch response: This repository is over its data quota. Account responsible for LFS bandwidth should purchase more data packs to restore access.
error: failed to fetch some objects from 'https://github.com/by256/icsg3d.git/info/lfs'

[by256]

Hi,

Apologies, I think this is an issue with git lfs on my end. I've put the saved models in a drive folder:

https://drive.google.com/file/d/1MTWl34Jp0io2dDcvRGOkESkrO6Vns8Pf/view?usp=sharing

Let me know if you have any issues accessing the files.

[MilesZhao]

Thank you so much! Just downloaded it!

[MilesZhao]

Another quick question, are your pre-trained models okay to generate other systems, like ABC6, except for perovskites? Because our work can generate different ternary materials of different systems, such as ABC6, ABC, ABC2, can I use your mixed model to generate different systems instead of training models for each system separately?

[cjcourt]

@MilesZhao Our mixed models can be used to generate different systems, this was shown in the original paper (Figure 6). However, since the mixed models were only trained on 3 system types (ABX3, AB, ABX2), it is anticipated that other generated systems will not be as high in quality. To generate a more diverse set of systems, I would encourage you to train the model on as diverse a set as possible.