Comments (2)
We are working on multi-GPU training in this PR: #105
I recommend you either wait a little longer until we merge it, or you can have a go trying it by checking out the fork in the PR. A few people have started testing it and it seems to work.
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Closing this as duplicate of #10, please use the PR #105 for now. For now you can either use a larger GPU or switch to a smaller model/batch size. Reducing the number of channels significantly helps with memory.
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Related Issues (20)
- Restart of the training using --restart_latest doesn't properly work - resolved -
- Deployment of the MACE Model Without Using ASE HOT 5
- Error while using multihead interface HOT 2
- Segmentation fault during LAMMPS-MACE-CPU run HOT 1
- Problems with parallelization on CPU (Using LAMMPS) HOT 1
- Improve plotting script
- Automatically add parameters to optimizer
- Change stress to virials internally
- ASE documentation update? HOT 4
- Move to ruff for linting and formating? HOT 5
- Tripeptides Data for MACE-OFF Model
- Bug on loading finetuning model HOT 2
- Remove `e3nn` version pin HOT 2
- models created from multihead fine tuning don't work in lammps HOT 7
- universal loss (at least in multi-head-interface branch) does not support per-config weight
- cannot turn off multihead finetuning in multi-head-interface branch HOT 18
- Colab Tutorial Link Does not work HOT 2
- help message for `--pair_repulsion` is wrong HOT 1
- How to use multi-GPUs training with PBS system HOT 21
- [feature suggest] active learning in lammps HOT 1
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