Update README.md

README.md

@@ -23,7 +23,7 @@ This model was pre-trained with 180MB of Lithuanian Wikipedia. The texts are tok
 ## Training
 The model was trained on wiki-corpus for 40 hours using NVIDIA Tesla P100 GPU.
 
-## How to use
+### How to use
 
 ### Load model
 
@@ -57,7 +57,9 @@ print(tokenizer.decode(outputs[0]))
 ## Limitations and bias
 The training data used for this model come from Lithuanian Wikipedia. We know it contains a lot of unfiltered content from the internet, which is far from neutral. As the openAI team themselves point out in their model card:
 
+```
 "Because large-scale language models like GPT-2 do not distinguish fact from fiction, we don’t support use-cases that require the generated text to be true. Additionally, language models like GPT-2 reflect the biases inherent to the systems they were trained on, so we do not recommend that they be deployed into systems that interact with humans > unless the deployers first carry out a study of biases relevant to the intended use-case. We found no statistically significant difference in gender, race, and religious bias probes between 774M and 1.5B, implying all versions of GPT-2 should be approached with similar levels of caution around use cases that are sensitive to biases around human attributes."
+```
 
 ## Author