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fairchem_uma_demo

Running on CPU Upgrade

zulissimeta commited on 29 days ago

Commit

450850c

1 Parent(s): 636045d

another stab

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app.py CHANGED Viewed

@@ -583,9 +583,8 @@ def main():
     * UMA models predict motion and behavior at the atomic scale, ultimately reducing the development cycle in molecular and materials discovery and unlocking new possibilities for innovation and impact.
     * UMA models are based on Density Functional Theory (DFT) training datasets. DFT simulations are a commonly used quantum chemistry method to simulate and understand behavior at the atomic scale.
     * UMA models are large mixture-of-linear-experts graph networks models trained on billions of atoms across five open-science simulation datasets released by the FAIR Chemistry team over the past 5 years. This demo uses the small UMA model with 146M total parameters, 32 experts, and 6M active parameters at any time to predict across all of these domains.
-    [Read the UMA paper for details](https://ai.meta.com/research/publications/uma-a-family-of-universal-models-for-atoms/)
-) or [download the UMA model](https://huggingface.co/facebook/UMA) and [FAIR Chemistry repository](https://github.com/facebookresearch/fairchem) to use this yourself!
     """
                         )
                     with gr.Accordion("Should I trust UMA?", open=False):

     * UMA models predict motion and behavior at the atomic scale, ultimately reducing the development cycle in molecular and materials discovery and unlocking new possibilities for innovation and impact.
     * UMA models are based on Density Functional Theory (DFT) training datasets. DFT simulations are a commonly used quantum chemistry method to simulate and understand behavior at the atomic scale.
     * UMA models are large mixture-of-linear-experts graph networks models trained on billions of atoms across five open-science simulation datasets released by the FAIR Chemistry team over the past 5 years. This demo uses the small UMA model with 146M total parameters, 32 experts, and 6M active parameters at any time to predict across all of these domains.
+    [Read the UMA paper for details](https://ai.meta.com/research/publications/uma-a-family-of-universal-models-for-atoms/) or [download the UMA model](https://huggingface.co/facebook/UMA) and [FAIR Chemistry repository](https://github.com/facebookresearch/fairchem) to use this yourself!
     """
                         )
                     with gr.Accordion("Should I trust UMA?", open=False):