Update app.py

app.py

@@ -50,25 +50,25 @@ examples = [
        "Maybe I'll fix it later. My friend is playing guitar in my room now. Sort of playing anyway.",
        "More like messing with it. He's still learning. There's a drawing on the wall next to me. "
     ),
-    (   "An open keyboard and buttons to push. The thing finally worked and I need not use periods, commas and all those thinks.",
+    (   "An open keyboard and buttons to push. The thing finally worked and I need not use periods, commas, and all those things.",
         "Double space after a period. We can't help it. I put spaces between my words and I do my happy little assignment of jibber-jabber.",
         "Babble babble babble for 20 relaxing minutes and I feel silly and grammatically incorrect. I am linked to an unknown reader.",
         "A graduate student with an absurd job. I type. I jabber and I think about dinoflagellates. About sunflower crosses and about ",
-        "the fiberglass that has be added to my lips via clove cigarettes and I think about things that I shouldn't be thinking.",
+        "the fiberglass that has to be added to my lips via clove cigarettes and I think about things that I shouldn't be thinking.",
         "I know I shouldn't be thinking. or writing let's say/  So I don't. Thoughts don't solidify. They lodge in the back. behind my tongue maybe.",
     )
 ]
 
-title = "Big Five Personality Traits Detection From Reviews Submitted"
-description = "The traditional machine learning models give a lot of pain when we do not have sufficient labeled data for the specific task or domain we care about to train a reliable model. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. We try to store this knowledge gained in solving the source task in the source domain and apply it to our problem of interest. In this work, I have utilized Transfer Learning utilizing BERT BASE UNCASED model to fine tune on Big-Five Personality traits Dataset."
-text1 = (
-    #"<center> Author: Owais Ahmad Data Scientist at <b> Thoucentric </b> <a href=\"https://www.linkedin.com/in/owaiskhan9654/\">Visit Profile</a> <br></center>"
+title = "Big Five Personality Traits Detection From Expository text features"
+description = ("In traditional machine learning, it can be challenging to train an accurate model if there is a lack of labeled data specific to the task or ",
+               "domain of interest. Transfer learning offers a way to address this issue by utilizing the pre-existing labeled data from a similar task or ",
+               "domain to improve model performance. By transferring knowledge learned from one task to another, transfer learning enables us to overcome ",
+               "the limitations posed by a shortage of labeled data, and to train more effective models even in data-scarce scenarios. We try to store this ",
+               "knowledge gained in solving the source task in the source domain and applying it to our problem of interest. In this work, I have utilized ",
+               "Transfer Learning utilizing BERT BASE UNCASED model to fine-tune on Big-Five Personality traits Dataset.")
+Fotter = (
     
-    # "<center> Model Trained GOOGLE COLAB Kernel <a href=\"https://colab.research.google.com/drive/1dbr9t9vxF8M80FAH9WoBFEdT0iGaXr1r?usp=sharing\">Link</a> <br></center>"
-        
-    # "<center> Kaggle Profile <a href=\"https://www.kaggle.com/owaiskhan9654\">Link</a> <br> </center>"
-    
-    "<center> HuggingFace Model Deployed Repository <a href=\"\"> Yet to be deployed</a> <br></center>"
+    "<center>&copy; 2023 Thoucentric </center>"
 )
 
 app = gr.Interface(
@@ -78,10 +78,10 @@ app = gr.Interface(
     examples=examples,
     title=title,
 	description=description,
-    article=text1,
+    article=Fotter,
     allow_flagging='never',
     analytics_enabled=False,
 )
 
 
-app.launch(inline=True,share=True, show_error=True)
+app.launch(inline=True,share=True, show_error=False)