Update README.md

README.md

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 # CLMBR-T-Base-Random
 
-This is a CLMBR model that was randomly initialized with a dummy vocabulary. 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.
+This is a CLMBR model with randomly initialized weights using a dummy vocabulary. 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 [the Clinical Language Modeling Based Representations paper (Steinberg et al. 2021)](https://www.sciencedirect.com/science/article/pii/S1532046420302653)
 
@@ -31,11 +31,11 @@ The weights are random, so **this model has no clinical or research use.**
 
 ## Uses
 
-This model generates dense representations for patients based on the structured data within their electronic health record. 
+This model generates (random) dense representations for patients based on the structured data within their electronic health record. 
 
 These representations can then be used for downstream tasks such as predicting diagnoses, detecting anomalies, or doing propensity score matching for causal inference.
 
-However, please note that **this version of the model has random weights.** Thus, the outputs will be random/meaningless.
+Again, please note that **this version of the model has random weights.** Thus, the outputs should be meaningless.
 
 
 ## How to Get Started with the Model