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import streamlit as st |
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline |
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tokenizer = AutoTokenizer.from_pretrained("impyadav/GPT2-FineTuned-Hinglish-Song-Generation") |
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model = AutoModelForCausalLM.from_pretrained("impyadav/GPT2-FineTuned-Hinglish-Song-Generation") |
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def get_song(line): |
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lyricist = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer |
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) |
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return lyricist(line, max_length=150, num_return_sequences=3) |
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if __name__ == '__main__': |
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st.title('AI Lyricist') |
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st.write('Transformer Architecture : {}'.format('gpt-2')) |
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st.subheader("Input") |
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user_input = st.text_area('', height=25) |
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result = get_song(user_input) |
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if st.button('Run'): |
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st.write(result) |
