Delete app.py

app.py

@@ -1,27 +0,0 @@
-
-import streamlit as st
-from transformers import pipeline, GPT2LMHeadModel, GPT2Tokenizer
-
-# Load pre-trained GPT-2 model and tokenizer
-model_name = "gpt2"
-model = GPT2LMHeadModel.from_pretrained(model_name)
-tokenizer = GPT2Tokenizer.from_pretrained(model_name)
-
-# Define function to generate blog post
-def generate_blogpost(topic):
-    input_text = f"Blog post about {topic}:"
-    input_ids = tokenizer.encode(input_text, return_tensors="pt")
-
-    # Generate text
-    output = model.generate(input_ids, max_length=500, num_return_sequences=1, no_repeat_ngram_size=2)
-
-    # Decode and return text
-    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
-    return generated_text
-
-# Example usage
-
-topic = "natural language processing"
-
-blogpost = generate_blogpost(topic)
-print(blogpost)