app.py

from transformers import pipeline
import gradio as gr

model_checkpoint = "MuntasirHossain/bert-finetuned-ner"
model = pipeline("ner", model=model_checkpoint, aggregation_strategy="simple")


# def ner(text):
#     output = model(text)
#     return {"text": text, "entities": output}

def ner(text):
    a = ""
    results = model(text)
    for result in results:
        a += result['word'] + " : " + result['entity_group'] + ",  "
    a = a[0:len(a)-3] # removes the ',  ' at the end of text
    return a


description = "This AI model is trained to identify and classify named entities in unstructured text." 
title = "Named Entity Recognition"
theme = "grass"
examples=["Mount Everest is Earth's highest mountain, located in the Mahalangur Himal sub-range of the Himalayas. Edmund Hillary and Tenzing Norgay were the first climbers confirmed\
 to have reached the summit of Mount Everest on May 29, 1953."]

gr.Interface(fn=ner,
    inputs="textbox",
    outputs="text",
    # gr.Textbox(placeholder="Enter sentence here..."), 
    # gr.HighlightedText(),
    title=title,
    theme = theme,
    description=description,
    examples=examples,
).launch()