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import gradio as gr | |
from transformers import pipeline | |
# Load the NER pipeline | |
ner_pipeline = pipeline("ner", model="dslim/bert-base-NER", grouped_entities=True) | |
# Define the prediction function | |
def recognize_entities(text): | |
results = ner_pipeline(text) | |
return str(results) | |
# Gradio UI | |
iface = gr.Interface(fn=recognize_entities, | |
inputs=gr.Textbox(lines=5, placeholder="Enter your text here..."), | |
outputs="text", | |
title="Named Entity Recognition (NER)", | |
description="Using dslim/bert-base-NER model to identify named entities in text.") | |
# Launch | |
iface.launch() | |