Update app.py

app.py

@@ -1,29 +1,27 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load your text-generation model from HF
-# (change "YourUsername/YourModel" to whichever model you want to use)
-generator = pipeline("text-generation", model="gpt2")
+generator = pipeline(
+    "text-generation",
+    model="gpt2",
+    pad_token_id=50256  # crucial for GPT-2
+)
 
 def generate_cv(name, education, experience):
-    # Build a "prompt" for your model
     prompt = (
-        f"Generate a CV based on these details:\n"
+        f"Generate a CV:\n"
         f"Name: {name}\n"
         f"Education: {education}\n"
         f"Experience: {experience}\n"
         "CV:\n"
     )
+    # Use max_new_tokens=100 (or something smaller) for speed
+    outputs = generator(prompt, max_new_tokens=100)
+    return outputs[0]["generated_text"]
 
-    # Call the pipeline to generate text (you can tweak max_length, etc.)
-    outputs = generator(prompt, max_length=300)
-    cv_text = outputs[0]["generated_text"]
-    return cv_text
-
-# Create a Gradio interface with 3 textboxes as input
 demo = gr.Interface(
-    fn=generate_cv, 
-    inputs=["text", "text", "text"],  # or gr.Textbox(…), etc.
+    fn=generate_cv,
+    inputs=["text", "text", "text"],
     outputs="text",
     title="Automated CV Generator"
 )