Update README.md

README.md

@@ -11,6 +11,8 @@ pipeline_tag: text2text-generation
 - Input: `context` (e.g. news article)
 - Output: `question <sep> answer`
 
+This model generates **abstractive** answers following the RACE dataset. If you would like to have **extractive** questions/answers, you can use our model trained on SQuAD: https://huggingface.co/potsawee/t5-large-generation-squad-QuestionAnswer.
+
 ## Model Details
 
 t5-large model is fine-tuned to the RACE dataset where the input is the context/passage and the output is the question followed by the answer. This is the first component in the question generation pipeline (i.e. `g1`) in our [MQAG paper](https://arxiv.org/abs/2301.12307), 
@@ -18,7 +20,7 @@ or please refer to the GitHub repo of this project: https://github.com/potsawee/
 
 ## How to Use the Model
 
-Use the code below to get started with the model. 
+Use the code below to get started with the model. You can also set do_sample=True in generate() to obtain different question-answer pairs.
 
 ```python
 >>> from transformers import AutoTokenizer, AutoModelForSeq2SeqLM