Create app.py

app.py

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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()