Update app.py

app.py

@@ -45,28 +45,28 @@ def app_info():
 iface1 = gr.Interface(
     fn=app_info, inputs=None, outputs=['text'], title="General-Infomation",
     description='''
-    This app, powered by the IEQ-BERT model (sadickam/sdg-classification-bert), is for automating the classification of text concerning 
-    with respect to indoor environmetal quality (IEQ). IEQ refers to the quality of the indoor air, lighting, 
+    This app, powered by the IEQ-BERT model (ieq/IEQ-BERT), is for automating the classification of text with respect 
+    to indoor environmental quality (IEQ). IEQ refers to the quality of the indoor air, lighting, 
     temperature, and acoustics within a building, as well as the overall comfort and well-being of its occupants. It encompasses various 
     factors that can impact the health, productivity, and satisfaction of people who spend time indoors, such as office workers, students, 
-    patients, and residents. This app assigns five labels to any given text and a text may be assigned one or more labels. The five labels include
+    patients, and residents. This app assigns five labels to any given text; hence, a text may be assigned one or more labels. The five labels include
     the following:
     - Acoustic
     - Indoor air quality (IAQ)
-    - No IEQ (label assigned when no IEQ is defected)
+    - No IEQ (label assigned when no IEQ is detected)
     - Thermal
     - Visual
 
-    Because IEQ-BERT is capable of assigning one or more labels to a text, it is possible that the returned prediction like 
-    (Acoustic_No IEQ) or (NO IEQ_Thermal). These multiple predictions that include "No IEQ" may suggest lack of contextual 
-    clarity in the text and need manual review to affirm label. 
+    Because IEQ-BERT is capable of assigning one or more labels to a text, it is possible that the returned prediction, like 
+    (Acoustic_No IEQ) or (NO IEQ_Thermal). These multiple predictions that include "No IEQ" may suggest a lack of contextual 
+    clarity in the text and need manual review to confirm the label. 
 
     This app has two analysis modules summarised below:
-    - Single-Text-Prediction - Analyses text pasted in a text box and return IEQ prediction.
+    - Single-Text-Prediction - Analyses text pasted in a text box and returns IEQ prediction.
     - Multi-Text-Prediction - Analyses multiple rows of texts in an uploaded CSV or Excell file and returns a downloadable CSV file with IEQ prediction for each row of text.
 
-    This app runs on a free server and may therefore not be suitable for analysing large CSV files. 
-    If you need assistance with analysing large CSV, do get in touch using the contact information in the Contact section.
+    This app runs on a free server and may, therefore, not be suitable for analysing large CSV files. 
+    If you need assistance with analysing large CSV files, use the contact information in the Contact section to get in touch.
 
     <h3>Contact</h3>
     <p>We would be happy to receive your feedback regarding this app. If you would also like to collaborate with us to explore some use cases for the model