Upload app.py
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app.py
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import streamlit as st
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from transformers import GPT2LMHeadModel, GPT2Tokenizer
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def app():
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st.title("์๋ ์ผ๊ธฐ ์์ฑ๊ธฐ")
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keywords = st.text_input("5๊ฐ์ ํค์๋๋ฅผ ์
๋ ฅํ์ธ์ (์ผํ๋ก ๊ตฌ๋ถ)", "")
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keyword_list = [kw.strip() for kw in keywords.split(",")]
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if len(keyword_list) == 5 and st.button("์ผ๊ธฐ ์ฐ๊ธฐ"):
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# ๋ชจ๋ธ ๋ฐ ํ ํฌ๋์ด์ ๋ก๋
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model = GPT2LMHeadModel.from_pretrained("gpt2")
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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# ํค์๋ ๊ธฐ๋ฐ fine-tuning
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input_ids = tokenizer.encode(" ".join(keyword_list), return_tensors="pt")
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output = model.generate(input_ids, max_length=500, num_return_sequences=1, do_sample=True, top_k=50, top_p=0.95, num_beams=5)
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# ์์ฑ๋ ์ผ๊ธฐ ์ถ๋ ฅ
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diary = tokenizer.decode(output[0], skip_special_tokens=True)
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st.write(diary)
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if __name__ == "__main__":
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app()
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