Update app.py

app.py

@@ -1,27 +1,27 @@
-import streamlit as st
+import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
 tokenizer = AutoTokenizer.from_pretrained("ahmadmac/Pretrained-GPT2")
 model = AutoModelForCausalLM.from_pretrained("ahmadmac/Pretrained-GPT2")
-
+temp
 def generate_text(prompt, max_length=50, num_return_sequences=1, temperature=0.7):
   input_ids = tokenizer(prompt, return_tensors="pt").input_ids
   output = model.generate(
       input_ids,
       max_length=max_length,
       num_return_sequences=num_return_sequences,
-      temperature=0.7  
+      temperature=temperature   
 
   )
   return tokenizer.decode(output[0], skip_special_tokens=True)
 
-def main():
-  st.title("Text Generator")
-  prompt = st.text_input("Enter your prompt:")
-  if st.button("Generate"):
-    generated_text = generate_text(prompt)
-    st.text_area("Generated Text:", generated_text)
+hface = gr.Interface(
+    fn=generate_text,
+    inputs="text",
+    outputs="text",
+    title="Text Generator",
+    description="Enter your prompt and generate text"
+)
 
-if __name__ == "__main__":
-  main()
+hface.launch()