Update app.py

app.py

@@ -3,6 +3,7 @@ from huggingface_hub import HfApi
 import spaces
 import shutil
 import logging
+import subprocess
 
 @spaces.GPU
 
@@ -42,6 +43,15 @@ def merge_and_upload(base_model, model_to_merge, scaling_factor, weight_drop_pro
     # Upload the result to Hugging Face Hub
     api = HfApi(token=token)
     try:
+        # Get the username of the user who is logged in
+        user = api.whoami(token=token)["name"]
+
+        # Autofill the repo name if none is provided
+        if not repo_name:
+            repo_name = f"{user}/default-repo"
+        else:
+            repo_name = repo_name
+
         # Create a new repo or update an existing one
         api.create_repo(repo_id=repo_name, token=token, exist_ok=True)
         
@@ -62,18 +72,22 @@ def merge_and_upload(base_model, model_to_merge, scaling_factor, weight_drop_pro
 # Define the Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Model Merger and Uploader")
-    token = gr.Textbox(label="Hugging Face Token", type="password")
-    base_model = gr.Textbox(label="Base Model")
-    model_to_merge = gr.Textbox(label="Model to Merge")
-    scaling_factor = gr.Slider(minimum=0, maximum=10, value=3.0, label="Scaling Factor")
-    weight_drop_prob = gr.Slider(minimum=0, maximum=1, value=0.3, label="Weight Drop Probability")
-    repo_name = gr.Textbox(label="Repo Name")
-    output = gr.Textbox(label="Output")
+    gr.Markdown("Combine capabilities from multiple models. Works with:")
+    gr.Markdown("* Stable Diffusion (1.5, XL/XL Turbo)")
+    gr.Markdown("* LLMs (Mistral, Llama, etc)")
+    gr.Markdown("* LoRas (must be same size)")
+    gr.Markdown("* Any two homologous models")
+    
+    with gr.Column():
+        gr.Textbox(label="Hugging Face Token", type="password")
+        gr.Textbox(label="Base Model")
+        gr.Textbox(label="Model to Merge")
+        gr.Slider(minimum=0, maximum=10, value=3.0, label="Scaling Factor")
+        gr.Slider(minimum=0, maximum=1, value=0.3, label="Weight Drop Probability")
+        gr.Textbox(label="Repo Name (leave blank for default)")
+        gr.Button("Merge and Upload")
     
-    gr.Button("Merge and Upload").click(
-        merge_and_upload,
-        inputs=[base_model, model_to_merge, scaling_factor, weight_drop_prob, repo_name, token],
-        outputs=output
-    )
+    with gr.Column():
+        gr.Textbox(label="Output")
 
 demo.launch()