asd

app.py

@@ -2,7 +2,7 @@ import json
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from peft import PeftModel, PeftConfig
-from huggingface_hub import HfApi, Repository
+from huggingface_hub import HfApi
 import gradio as gr
 
 # Global variables to store the model and tokenizer
@@ -74,21 +74,20 @@ def run_merge_and_push():
 
 # Gradio interface
 with gr.Blocks() as demo:
-    with gr.TabbedInterface(["Generate Text", "Merge and Push"]) as tabs:
-        with tabs[0]:
-            iface = gr.Interface(
-                fn=generate_text,
-                inputs=gr.Textbox(lines=5, label="Input Text"),
-                outputs=gr.Textbox(lines=10, label="Generated Text"),
-                title="Merged Llama 3 8B Instruct Model",
-                description="Enter text to generate a response from the merged model.",
-            )
-            iface.launch()
-        
-        with tabs[1]:
-            merge_and_push_button = gr.Button("Merge Models and Push to Hub")
-            merge_and_push_output = gr.Textbox(lines=20, label="Merge and Push Output")
-            merge_and_push_button.click(run_merge_and_push, outputs=merge_and_push_output)
+    with gr.Tab("Generate Text"):
+        iface = gr.Interface(
+            fn=generate_text,
+            inputs=gr.Textbox(lines=5, label="Input Text"),
+            outputs=gr.Textbox(lines=10, label="Generated Text"),
+            title="Merged Llama 3 8B Instruct Model",
+            description="Enter text to generate a response from the merged model.",
+        )
+        iface.launch()
+    
+    with gr.Tab("Merge and Push"):
+        merge_and_push_button = gr.Button("Merge Models and Push to Hub")
+        merge_and_push_output = gr.Textbox(lines=20, label="Merge and Push Output")
+        merge_and_push_button.click(run_merge_and_push, outputs=merge_and_push_output)
 
 # Launch the interface
 if __name__ == "__main__":