Update README.md

README.md

@@ -117,9 +117,9 @@ Model ID                                 | NASBench101  | ENAS  | NASNet
 akhauriyash/RegressLM-gemma-s-RLM-table3 | 0.384        | 0.211 | 0.209 
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-Credits
+## Credits
 
-This dataset was collated from several graph/NAS sources, along with our own profiling where applicable. Please credit and cite the original datasets accordingly.
+This dataset was collated from several graph/NAS sources, along with our own profiling where applicable. We export and generate the ONNX descriptions of all architectures in our dataset. Please credit and cite the original datasets accordingly.
 
 Inception, Hiaml, Ofa-MB/PN/RN, Twopath: `
 Mills, K. G., Han, F. X., Zhang, J., Chudak, F., Mamaghani, A. S., Salameh, M., Lu, W., Jui, S., & Niu, D. (2023). Gennape: Towards generalized neural architecture performance estimators. Proceedings of the AAAI Conference on Artificial Intelligence, 37(8), 9190–9199.`
@@ -145,7 +145,7 @@ Lee, Hayeon, et al. "Help: Hardware-adaptive efficient latency prediction for na
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-Citations
+## Citations
 
 If you found this dataset useful for your research, please cite the original sources above as well as: