Project By: Bishal Debb Pande
Supervisor: Dr. Aman Shakya
Model Overview
This model is a Named Entity Recognition (NER) model fine-tuned on the Everest NER dataset, which is a dataset for recognizing named entities in Nepali text. The base model used for fine-tuning is xlm-roberta-base, a multilingual transformer model that supports over 100 languages.
How to Use
Go to: https://huggingface.co/bishaldpande/Ner-xlm-roberta-base
Then you can use this model with the Hugging Face transformers library as follows:
from transformers import pipeline
# Load the NER pipeline
ner = pipeline(“ner”, model=”bishaldpande/Ner-xlm-roberta-base”) # Example input
text = “सगरमाथा विश्वको अग्लो हिमाल हो।”
# Perform NER
entities = ner(text)
print(entities)
Project Github
URL: https://github.com/bishaldpande/ner_web/tree/app