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import streamlit as st | |
import transformers | |
# Load the pre-trained NER model | |
model = transformers.pipeline('ner', model='dslim/bert-base-NER') | |
# Define the Streamlit app | |
def app(): | |
# Set the app title | |
st.title('Named Entity Recognition with HuggingFace') | |
# Define the input text area | |
text = st.text_area('Enter some text:', value='', height=200) | |
# Define the button to submit the text | |
if st.button('Submit'): | |
# Run the NER model on the input text | |
entities = model(text) | |
# Display the named entities in the input text | |
for entity in entities: | |
st.write(f'{entity["entity"]}: {entity["word"]}') | |
# Run the Streamlit app | |
if __name__ == '__main__': | |
app() | |