new model

app.py

@@ -1,13 +1,11 @@
 import gradio as gr
 from transformers import pipeline
 
-# Use a small model to start (you can swap later for stronger ones like Mixtral)
-pipe = pipeline("text-generation", model="mistralai/Mixtral", max_new_tokens=200)
+pipe = pipeline("text-generation", model="gpt2", max_new_tokens=200)
 
 def explain_code(code, level):
     prompt = f"Explain what the following {level.lower()} code does:\n\n{code}\n\nExplanation:"
     result = pipe(prompt)[0]["generated_text"]
-    # Strip the prompt part off to clean the output
     explanation = result[len(prompt):].strip()
     return explanation
 
@@ -19,10 +17,7 @@ iface = gr.Interface(
     ],
     outputs=gr.Textbox(label="Explanation", lines=8),
     title="💡 Code Explainer",
-    description=(
-        "Enter code and get a natural language explanation. "
-        "Powered by a Hugging Face text-generation model."
-    ),
+    description="Enter code and get a natural language explanation.",
     theme="soft",
     examples=[
         ["for i in range(5): print(i*i)", "Python"],