app.py

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",
    examples=[
        ["Adventurer is approached by a mysterious stranger in the tavern for a new quest."],
        ["He didn't remember the last time he had to run this fast as he jumped on to the bus."],
        ["Fate has it's own plans for the common man, which is why we philosophise on the observationg giving it our own interpretation."],
        ["The bear reached the river and spotted a school of fish. His hunger started taking its toll."]
    ],
    inputs=[gr.Textbox(lines=7, label="Text")],
    outputs=[gr.Textbox(lines=7, label="Story NER")]
)

demo.launch(share=True)