Update app.py

app.py

@@ -1,5 +1,3 @@
-#build theme
-
 import gradio as gr
 
 def chat1(message,history):
@@ -17,27 +15,91 @@ chatbot = gr.Chatbot()
 chatbot1 = gr.Chatbot()
 chatbot2 = gr.Chatbot()
 
-with gr.Blocks() as demo:
-    gr.Markdown("Efficient Fine Tuning - Bert Model for Text Classification")
-    #============================ ADD YOUR NAME ON LINE BELOW (LAST PERSON CAN REMOVE THIS COMMENT) ============================#
-    gr.Markdown("By: Greylyn | Rahul | Rajevan | <Member 4>")
-    
-    with gr.Row():
-        with gr.Column():
-            inp = gr.Textbox(placeholder="Prompt",label= "Enter Query")
-            btn = gr.Button("Run")
+with gr.Blocks(
+    title="",
 
+) as demo:
+    gr.Markdown("""
+        <div style="overflow: hidden;color:#fff;display: flex;flex-direction: column;align-items: center; position: relative; width: 100%; height: 180px;background-size: cover; background-image: url(https://www.grssigns.co.uk/wp-content/uploads/web-Header-Background.jpg);">
+            <img style="width: 130px;height: 60px;position: absolute;top:10px;left:10px" src="https://www.torontomu.ca/content/dam/tmumobile/images/TMU-Mobile-AppIcon.png"/>
+            <span style="margin-top: 40px;font-size: 36px ;font-family:fantasy;">Efficient Fine tuning Of Large Language Models</span>
+            <span style="margin-top: 10px;font-size: 14px;">By: Rahul Adams, Gerylyn Gao, Rajevan Lograjh & Mahir Faisal</span>
+            <span style="margin-top: 5px;font-size: 14px;">Group Id: AR06 FLC: Alice Reuada</span>
+        </div>
+    """)
+    with gr.Tab("Text Classification"):
+        with gr.Row():
+            gr.Markdown("<h1>Efficient Fine Tuning for Text Classification</h1>")
         with gr.Row():
-            with gr.Column():
-                out = gr.Textbox()
-            with gr.Column():    
-                out1 = gr.Textbox()
-            with gr.Column():
-                out2 = gr.Textbox()
-
-    btn.click(fn=chat1, inputs=inp, outputs=out)
-    btn.click(fn=chat1, inputs=inp, outputs=out1)
-    btn.click(fn=chat1, inputs=inp, outputs=out2)
+            with gr.Column(scale=0.3):
+                inp = gr.Textbox(placeholder="Prompt",label= "Enter Query")
+                btn = gr.Button("Run")
+                gr.Markdown("""
+                            <p>Model: Tiny Bert <br>
+                            NLP Task: Text Classification <br>
+                            Dataset: IMDB Movie review dataset for sentiment analysis</p>
+                            <p>insert information on training parameters here</p>
+                            """)
+
+            with gr.Row():
+                with gr.Column():
+                    out = gr.Textbox(label= " Untrained Model")
+                with gr.Column():    
+                    out1 = gr.Textbox(label= " Conventionaly Fine Tuned Model")
+                with gr.Column():
+                    out2 = gr.Textbox(label= " LoRA fine Tuned Model")
+
+        btn.click(fn=chat1, inputs=inp, outputs=out)
+        btn.click(fn=chat1, inputs=inp, outputs=out1)
+        btn.click(fn=chat1, inputs=inp, outputs=out2)
+
+    with gr.Tab("Natrual Language Infrencing"):
+         with gr.Row():
+             gr.Markdown("<h1>Efficient Fine Tuning for Natual Languae Infrencing</h1>")
+         with gr.Row():
+            with gr.Column(scale=0.3):
+                inp = gr.Textbox(placeholder="Prompt",label= "Enter Query")
+                btn = gr.Button("Run")
+                gr.Markdown("""
+                            <p>Model: ELECTRA Bert Small <br>
+                            NLP Task: Natual Languae Infrencing <br>
+                            Dataset: Stanford Natural Language Inference Dataset</p>
+                            <p>insert information on training parameters here</p>
+                            """)
+
+            with gr.Row():
+                with gr.Column():
+                    out = gr.Textbox(label= " Untrained Model")
+                with gr.Column():    
+                    out1 = gr.Textbox(label= " Conventionaly Fine Tuned Model")
+                with gr.Column():
+                    out2 = gr.Textbox(label= " LoRA fine Tuned Model")
+
+    with gr.Tab("Sematic Text Similarity"):
+         with gr.Row():
+             gr.Markdown("<h1>Efficient Fine Tuning for Semantic Text Similarity</h1>")
+         with gr.Row():
+            with gr.Column(scale=0.3):
+                inp = gr.Textbox(placeholder="Prompt",label= "Enter Query")
+                btn = gr.Button("Run")
+                gr.Markdown("""
+                            <p>Model: Tiny Bert <br>
+                            NLP Task: Text Classification <br>
+                            Dataset: IMDB Movie review dataset for sentiment analysis</p>
+                            <p>insert information on training parameters here</p>
+                            """)
+
+            with gr.Row():
+                with gr.Column():
+                    out = gr.Textbox(label= " Untrained Model")
+                with gr.Column():    
+                    out1 = gr.Textbox(label= " Conventionaly Fine Tuned Model")
+                with gr.Column():
+                    out2 = gr.Textbox(label= " LoRA fine Tuned Model")
+
+    with gr.Tab("More information"):
+        gr.Markdown("stuff to add")
+
 
 if __name__ == "__main__":
     demo.launch()