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import gradio as gr | |
from transformers import pipeline | |
def generate_story(story): | |
ner = pipeline("ner", model="dbmdz/bert-large-cased-finetuned-conll03-english") | |
return str(ner(story)) | |
demo = gr.Interface ( | |
fn=generate_story, | |
description="Named Entity Recognition Demo with BERT (dbmdz/bert-large-cased-finetuned-conll03-english)", | |
examples=[ | |
["England won the 2019 world cup vs The 2019 world cup happened in England."], | |
["Washington is the capital of the US vs The first president of the US was Washington."], | |
["My name is Ganesh Kamath and I work at AMD in Bangalore."] | |
], | |
inputs=[gr.Textbox(lines=7, label="Text")], | |
outputs=[gr.Textbox(lines=7, label="Story NER")] | |
) | |
demo.launch(share=True) |