souvikmaji22's picture
Create app.py
362dfd9 verified
raw
history blame
639 Bytes
import gradio as gr
from transformers import pipeline
get_completion = pipeline("ner", model="dslim/bert-base-NER")
def ner(input):
output = get_completion(input)
return {"text": input, "entities": output}
gr.close_all()
demo = gr.Interface(fn=ner,
inputs=[gr.Textbox(label="Text to find entities", lines=2)],
outputs=[gr.HighlightedText(label="Text with entities")],
title="NER with dslim/bert-base-NER",
description="Find entities using the `dslim/bert-base-NER` model under the hood!",
allow_flagging="never",
)
demo.launch()