Update app.py

app.py

@@ -5,7 +5,8 @@ from scipy.io import arff
 
 rtf_model = REaLTabFormer(
     model_type="tabular",
-    gradient_accumulation_steps=1)
+    epochs=50,
+    gradient_accumulation_steps=4)
 
 
 def generate_data(file, num_samples):
@@ -103,11 +104,11 @@ with gr.Blocks(css = css) as demo:
     gr.Markdown("""
                 ## REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers
             """)
-    # gr.HTML('''
-    #  <p style="margin-bottom: 10px; font-size: 94%">
-    #             Whisper is a general-purpose speech recognition model released by OpenAI that can perform multilingual speech recognition as well as speech translation and language identification. Combined with an emotion detection model,this allows for detecting emotion directly from speech in multiple languages and can potentially be used to analyze sentiment from customer calls. It could also be used to transcribe and detect different emotions to enable a data-driven analysis for psychotherapy.
-    #           </p>
-    #           ''')
+    gr.HTML('''
+     <p style="margin-bottom: 10px; font-size: 94%">
+                This is an unofficial demo for REaLTabFormer that can be used to generate synthetic data from single tabular data using GPT. The demo is based on the <a href='https://github.com/avsolatorio/REaLTabFormer' style='text-decoration: underline;' target='_blank'> Github </a> implementation provided by the authors.
+              </p>
+              ''')
     
     with gr.Column():
             #gr.Markdown(""" ### Record audio """)