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README.md

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 This is a CLMBR model that was "pretrained" on **synthetic data**. The purpose of this model is to test code pipelines and demonstrate how to use CLMBR before applying for access to the official CLMBR release that was trained on real Stanford Hospital data.
 
-The model architecture is CLMBR-T-Base (144M params), as originally described in [the EHRSHOT paper (Wornow et al. 2023)](https://arxiv.org/abs/2307.02028), and based on the architecture originally developed in [(Steinberg et al. 2021)](https://www.sciencedirect.com/science/article/pii/S1532046420302653)
+The model architecture is CLMBR-T-Base (144M params), as originally described in [the EHRSHOT paper (Wornow et al. 2023)](https://arxiv.org/abs/2307.02028), and based on the architecture originally developed in [the Clinical Language Modeling Based Representations paper (Steinberg et al. 2021)](https://www.sciencedirect.com/science/article/pii/S1532046420302653)
 
 The synthetic data used for training is uniformly sampled random data with no intrinsic signal, so **this model has no clinical or research use.**