Update README.md

README.md

@@ -8,7 +8,7 @@ The model consists of 12 layers with a model dimension of 768, and a feedforward
 # Training data
 GPT-J 162B was pre-trained on the Pile, a large-scale curated dataset created by EleutherAI. It was then finetuned on synthetically generated data that was procedurally generated using the Rhinocers/Grasshopper software suite. The model was finetuned for 1.25 billion tokens over 11,500 steps on TPU v3-8. It was trained as an autoregressive language model, using cross-entropy loss to maximize the likelihood of predicting the next token correctly.  
 
-#Intended Use and Limitations
+# Intended Use and Limitations
 Architext models learn an inner representation of the architectural design that can be used to generate a larger diversity of geometric designs and can be useful for many downstream design workflows and tasks. While it could be adapted to many different design outputs, the model is best at generating residential floor plans given a natural language prompt.
 
 # How to use
@@ -45,5 +45,5 @@ To cite the codebase that trained this model:
   month = May
 }
 
-#Acknowledgements
+# Acknowledgements
 This project would not have been possible without compute generously provided by Google through the TPU Research Cloud that generously provided access to Clout TPU VMs used to finetune this model.