Update README.md

README.md

@@ -29,3 +29,15 @@ pipeline = MyToxicityDebiaserPipeline(
 text = "Your example text here"
 result = pipeline(text)
 print(result)
+```
+
+## Tips
+Here are some tips for tuning the GPT2 model to improve the quality of its generated prompts:
+
+-max_length: This parameter controls the maximum length of the generated prompt. You can experiment with different values to find the best length that suits your needs. A longer length may result in more context, but it may also make the prompt less coherent.
+
+-top_p: This parameter controls the diversity of the generated prompt. A lower value of top_p will generate more conservative and predictable prompts, while a higher value will generate more diverse and creative prompts. You can experiment with different values to find the right balance.
+
+-temperature: This parameter controls the randomness of the generated prompt. A lower value of temperature will generate more conservative and predictable prompts, while a higher value will generate more diverse and creative prompts. You can experiment with different values to find the right balance.
+
+As for the prompt, you can try different prompts to see which one works better for your specific use case. You can also try pre-processing the input text to remove any bias or offensive language before passing it to the GPT2 model. Additionally, you may want to consider fine-tuning the GPT2 model on your specific task to improve its performance.