Update app.py

app.py

@@ -11,13 +11,12 @@ def main():
     We include the output from four different models, the [BART-Large](https://huggingface.co/dhmeltzer/bart-large_askscience-qg) and [FLAN-T5-Base](https://huggingface.co/dhmeltzer/flan-t5-base_askscience-qg) models \
     fine-tuned on the r/AskScience split of the [ELI5 dataset](https://huggingface.co/datasets/eli5) as well as the zero-shot output \
     of the [FLAN-T5-XXL](https://huggingface.co/google/flan-t5-xxl) model and the [GPT-3.5-turbo](https://platform.openai.com/docs/models/gpt-3-5) model.\
-    \n\n For a more thorough discussion of question generation see this [report](https://wandb.ai/dmeltzer/Question_Generation/reports/Exploratory-Data-Analysis-for-r-AskScience--Vmlldzo0MjQwODg1?accessToken=fndbu2ar26mlbzqdphvb819847qqth2bxyi4hqhugbnv97607mj01qc7ed35v6w8) for EDA on the r/AskScience dataset and this \
+    For a more thorough discussion of question generation see this [report](https://wandb.ai/dmeltzer/Question_Generation/reports/Exploratory-Data-Analysis-for-r-AskScience--Vmlldzo0MjQwODg1?accessToken=fndbu2ar26mlbzqdphvb819847qqth2bxyi4hqhugbnv97607mj01qc7ed35v6w8) for EDA on the r/AskScience dataset and this \
     [report](https://api.wandb.ai/links/dmeltzer/7an677es) for details on our training procedure.\
     \n\nThe two fine-tuned models (BART-Large and FLAN-T5-Base) are hosted on AWS using a combination of AWS Sagemaker, Lambda, and API gateway.\
     GPT-3.5 is called using the OpenAI API and the FLAN-T5-XXL model is hosted by HuggingFace and is called with their Inference API.\
     \n \n **Disclaimer**: When first running this application it may take approximately 30 seconds for the first two responses to load because of the cold start problem with AWS Lambda.\
-    You may recieve also an error message when calling the FLAN-T5-XXL model since the Inference API takes around 20 seconds to load the model.\
-    Both issues should disappear on any subsequent calls to the application.")
+    The models will respond quicker on any subsequent calls to the application.")
     
     AWS_checkpoints = {}
     AWS_checkpoints['BART-Large']='https://8hlnvys7bh.execute-api.us-east-1.amazonaws.com/beta/'
@@ -44,7 +43,7 @@ def main():
     
     # User search
     user_input = st.text_area("Question Generator", 
-                                """Black holes are the most gravitationally dense objects in the universe.""")
+                                """Black holes can evaporate by emitting Hawking radiation.""")
     
     if user_input: