Create app.py

app.py

@@ -0,0 +1,42 @@
+import os
+import gradio as gr
+from transformers import AutoModel, AutoTokenizer
+
+def process_models(model_name, save_dir, additional_models):
+    log_lines = []
+    
+    # Process primary model
+    log_lines.append(f"🚀 Loading model: **{model_name}**")
+    try:
+        model = AutoModel.from_pretrained(model_name)
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+        model_save_path = os.path.join(save_dir, model_name.replace("/", "_"))
+        os.makedirs(model_save_path, exist_ok=True)
+        model.save_pretrained(model_save_path)
+        log_lines.append(f"✅ Saved **{model_name}** to `{model_save_path}`")
+    except Exception as e:
+        log_lines.append(f"❌ Error with **{model_name}**: {e}")
+    
+    # Process additional models if any
+    if additional_models:
+        for m in additional_models:
+            log_lines.append(f"🚀 Loading model: **{m}**")
+            try:
+                model = AutoModel.from_pretrained(m)
+                tokenizer = AutoTokenizer.from_pretrained(m)
+                model_save_path = os.path.join(save_dir, m.replace("/", "_"))
+                os.makedirs(model_save_path, exist_ok=True)
+                model.save_pretrained(model_save_path)
+                log_lines.append(f"✅ Saved **{m}** to `{model_save_path}`")
+            except Exception as e:
+                log_lines.append(f"❌ Error with **{m}**: {e}")
+    
+    return "\n".join(log_lines)
+
+# Mermaid glossary: a one-line flow summary of our UI actions.
+mermaid_glossary = """graph LR
+A[🚀 Model Input] --> B[Load Model]
+B --> C[💾 Save Model]
+D[🧩 Additional Models] --> B
+
+"""