Create app.py

app.py

@@ -0,0 +1,48 @@
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+import streamlit as st
+
+
+# Load the tokenizer and model
+tokenizer = GPT2Tokenizer.from_pretrained('webtoon_tokenizer')
+model = GPT2LMHeadModel.from_pretrained('webtoon_model')
+
+
+# Define the app
+def main():
+    st.title('Webtoon Description Generator')
+
+    # Get the input from the user
+    title = st.text_input('Enter the title of the Webtoon:', '')
+
+    # Generate the description
+    if st.button('Generate Description'):
+        with st.spinner('Generating...'):
+            description = generate_description(title)
+        st.success(description)
+
+
+# Define the function that generates the description
+def generate_description(title):
+    # Preprocess the input
+    input_text = f"{title.lower()}"
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
+
+    # Generate the output using the model
+    output = model.generate(
+        input_ids=input_ids,
+        max_length=256,
+        num_beams=4,
+        early_stopping=True,
+        no_repeat_ngram_size=2
+    )
+
+    # Convert the output to text
+    description = tokenizer.decode(output[0], skip_special_tokens=True)
+
+    return description
+
+
+if __name__ == '__main__':
+    main()