# Pretrained models

:::{margin}
```{image} ../assets/icons/inorganic.svg
:alt: Inorganic Materials
:width: 100px
```
:::

:::{tip} Recommended Model
**2025 recommendation:** We suggest using the [UMA model](../core/uma), trained on all of the FAIR chemistry datasets. UMA provides state-of-the-art accuracy, energy conservation, and will continue to receive updates.
:::

The UMA model has a number of nice features over the previous checkpoints:
1. It is state-of-the-art in out-of-domain prediction accuracy
2. The UMA small model is an energy conserving and smooth checkpoint, so should work much better for vibrational calculations, molecular dynamics, etc.
3. The UMA model is most likely to be updated in the future.

## Legacy OMat pretrained models

:::{note}
These checkpoints are included here for baselining and model reproducibility. For new projects, we recommend using UMA.
::: 

* All config files for the OMat24 models are available in the [`configs/omat24`](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24) directory.
* All models are equiformerV2 S2EFS models

**Note** in order to download any of the model checkpoints from the links below, you will need to first request access
through the [OMAT24 Hugging Face page](https://huggingface.co/fairchem/OMAT24).

These checkpoints are trained on OMat24 only. Note that predictions are *not* Materials Project compatible.

| Model Name            | Checkpoint	| Config                                                                                      |
|-----------------------|--------------|---------------------------------------------------------------------------------------------|
| EquiformerV2-31M-OMat | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_31M_omat.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/all/eqV2_31M.yml)   |
| EquiformerV2-86M-OMat | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_86M_omat.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/all/eqV2_86M.yml)   |
| EquiformerV2-153M-OMat | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_153M_omat.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/all/eqV2_153M.yml)  |


## MPTrj only models
These models are trained only on the [MPTrj](https://figshare.com/articles/dataset/Materials_Project_Trjectory_MPtrj_Dataset/23713842) dataset.

| Model Name                | Checkpoint	| Config                                                                          |
|---------------------------|--------------|---------------------------------------------------------------------------------|
| EquiformerV2-31M-MP       | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_31M_mp.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/mptrj/eqV2_31M_mptrj.yml) |
| EquiformerV2-31M-DeNS-MP  | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_dens_31M_mp.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/mptrj/eqV2_31M_dens_mptrj.yml) |
| EquiformerV2-86M-DeNS-MP  | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_dens_86M_mp.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/mptrj/eqV2_86M_dens_mptrj.yml) |
| EquiformerV2-153M-DeNS-MP | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_dens_153M_mp.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/mptrj/eqV2_153M_dens_mptrj.yml) |


## Finetuned OMat models
These models are finetuned from the OMat pretrained checkpoints using MPTrj or MPTrj and sub-sampled trajectories
from the 3D PBE Alexandria dataset, which we call Alex.

| Model Name                     | Checkpoint	| Config                                                                             |
|--------------------------------|--------------|------------------------------------------------------------------------------------|
| EquiformerV2-31M-OMat-Alex-MP  | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_31M_omat_mp_salex.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/finetune/eqV2_31M_ft_salexmptrj.yml) |
| EquiformerV2-86M-OMat-Alex-MP  | [checkpoint](https://huggingface.co/fairchem/OMAT24/blob/main/eqV2_86M_omat_mp_salex.pt) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/finetune/eqV2_86M_ft_salexmptrj.yml) |
| EquiformerV2-153M-OMat-Alex-MP | [checkpoint](https://huggingface.co/fairchem/OMAT24) | [config](https://github.com/facebookresearch/fairchem/tree/main/configs/omat24/finetune/eqV2_153M_ft_salexmptrj.yml) |


Please consider citing the following work if you use OMat24 models in your work,
```bibtex
@article{barroso-luqueOpenMaterials20242024,
    title = {Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models},
    author = {Barroso-Luque, Luis and Shuaibi, Muhammed and Fu, Xiang and Wood, Brandon M. and Dzamba, Misko and Gao, Meng and Rizvi, Ammar and Zitnick, C. Lawrence and Ulissi, Zachary W.},
    date = {2024-10-16},
    eprint = {2410.12771},
    eprinttype = {arXiv},
    doi = {10.48550/arXiv.2410.12771},
    url = {http://arxiv.org/abs/2410.12771},
}
```