Update README.md

README.md

@@ -4,7 +4,7 @@ license: mit
 LoRA weights only and trained for research - nothing from the foundation model. Trained using Open-Assistant's dataset. Shout-out to Open-Assistant and LAION for giving us early research access to the dataset.
 
 Sample usage
-
+```python
 import torch
 import os
 import transformers
@@ -32,7 +32,7 @@ with torch.no_grad():
         temperature=1.0
     )
 print(tokenizer.decode(out[0]))
-
+```
 The model will continue the conversation between the user and itself. If you want to use as a chatbot you can alter the generate method to include stop sequences for 'User:' and 'Assistant:' or strip off anything past the assistant's original response before returning.
 
 Trained for 4 epochs with a sequence length of 2048 on 8 A6000s with an effective batch size of 120.