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LegendaryToe
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ec6901a
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Parent(s):
6668c8f
cp
Browse files- app.py +14 -5
- requirements.txt +3 -0
app.py
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import streamlit as st
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import streamlit as st
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from transformers import pipeline
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# Load your model; this example uses the GPT-2 model for text generation.
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generator = pipeline('text-generation', model='gpt2')
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st.title('Hugging Face Model Integration')
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# Text input
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user_input = st.text_input("Type a sentence to complete", "Streamlit is ")
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# Generate text button
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if st.button('Generate'):
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# Generate text
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result = generator(user_input, max_length=50, num_return_sequences=1)
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# Display the generated text
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st.text_area("Generated Text", result[0]['generated_text'], height=150)
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requirements.txt
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streamlit
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streamlit
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transformers
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torch
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