Create app.py

app.py

@@ -0,0 +1,26 @@
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the GPT-2 large model and tokenizer
+model_name = "gpt2-large"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def generate_blogpost(topic):
+    input_text = f"Write a blog post about {topic}:"
+    inputs = tokenizer.encode(input_text, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=500, num_return_sequences=1)
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return generated_text
+
+# Streamlit UI
+st.title("Blog Post Generator")
+st.write("Generate a blog post for a given topic using GPT-2 large.")
+
+topic = st.text_input("Enter the topic:")
+if st.button("Generate"):
+    if topic:
+        blog_post = generate_blogpost(topic)
+        st.write(blog_post)
+    else:
+        st.write("Please enter a topic to generate a blog post.")