from transformers import pipeline
import torch

ner_model = pipeline('ner')

model_checkpoint = "huggingface-course/bert-finetuned-ner"
classifier = pipeline("token-classification", model=model_checkpoint, aggregation_strategy="simple")

device = "cuda:0" if torch.cuda.is_available() else "cpu"

def perform_ner(text):
    # Your NER function implementation goes here
    # Replace this with your own checkpoint
    result = classifier(text)
    return {"entities": [result]}