| # import streamlit as st | |
| # | |
| # x = st.slider('Select a value') | |
| # st.write(x, 'squared is', x * x) | |
| import streamlit as st | |
| from transformers import pipeline | |
| st.write("Starting the app") | |
| # Load a pre-trained pipeline for text generation | |
| generator = pipeline('text-generation', model='gpt2') | |
| st.title('Simple Hugging Face Space with Streamlit') | |
| # Text input widget | |
| input_text = st.text_area('Enter your text here:', '') | |
| if st.button('Generate'): | |
| if input_text: | |
| # Generate text using the model | |
| outputs = generator(input_text, max_length=50, num_return_sequences=1) | |
| st.write('Generated Text:') | |
| st.write(outputs[0]['generated_text']) | |
| else: | |
| st.write('Please enter some text to generate.') | |
| # if __name__ == '__main__': | |
| # st.title('ACR') | |