Add pipeline tag, library name, and paper link

README.md

@@ -1,6 +1,8 @@
 ---
 license: apache-2.0
 license_link: LICENSE
+pipeline_tag: graph-ml
+library_name: torchmd-net
 tags:
 - chemistry
 - molecular simulations
@@ -15,6 +17,8 @@ tags:
 **Contact:** info@acellera.com  
 **License:** apache 2.0
 
+This model was presented in the paper [AceFF: A State-of-the-Art Machine Learning Potential for Small Molecules](https://huggingface.co/papers/2601.00581).
+
 ---
 
 ## Overview
@@ -101,4 +105,4 @@ More bechmarks coming soon in a pre-print, stay tuned...
 
 [2] Raul P. Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E. Markland, Gianni De Fabritiis, TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations, J. Chem. Theory Comput. 2024, 20, 10, 4076–4087, https://arxiv.org/abs/2402.17660
 
-[3] Francesc Sabanés Zariquiey, Stephen E. Farr, Stefan Doerr, Gianni De Fabritiis, QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials, https://arxiv.org/abs/2501.01811 (2025).
+[3] Francesc Sabanés Zariquiey, Stephen E. Farr, Stefan Doerr, Gianni De Fabritiis, QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials, https://arxiv.org/abs/2501.01811 (2025).