Create app.py

app.py

@@ -0,0 +1,22 @@
+import transformers
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+from transformers import GenerationConfig
+import streamlit as st
+
+model_name = "gpt2-large"
+model = GPT2LMHeadModel.from_pretrained(model_name)
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+
+title = st.text_area("\nEnter a title to generate a blog post:")
+
+input_prompt = f"Blog Title: {title}\n\nBlog Post:\n"
+input_ids = tokenizer.encode(input_prompt, return_tensors='pt')
+
+generation_config = GenerationConfig(max_new_tokens=100, do_sample=True, temperature=0.7)
+
+output_ids = model.generate(input_ids, generation_config=generation_config)[0]
+
+output_text = tokenizer.decode(output_ids, skip_special_tokens=True)
+
+if text:
+    st.write(output_text)