OMat24
A materials science model released by the FAIR Chemistry team.
CommonProductProductivityMaterials ScienceMachine Learning
OMat24 is a series of model checkpoints released by Meta's FAIR Chemistry team, differing in model size and training strategies. These models employ the EquiformerV2 architecture to advance research in materials science by predicting material properties through machine learning models, thereby accelerating the discovery and development of new materials. The models have been pretrained on public datasets and are available in various scales to meet different research needs.
OMat24 Visit Over Time
Monthly Visits
17788201
Bounce Rate
44.87%
Page per Visit
5.4
Visit Duration
00:05:32