Instructions to use Shushant/NepNewsBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shushant/NepNewsBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Shushant/NepNewsBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Shushant/NepNewsBERT") model = AutoModelForMaskedLM.from_pretrained("Shushant/NepNewsBERT") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
NepNewsBERT
Masked Language Model for nepali language trained on nepali news scrapped from different nepali news website. The data set contained about 10 million of nepali sentences mainly related to nepali news.
Usage
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("Shushant/NepNewsBERT")
model = AutoModelForMaskedLM.from_pretrained("Shushant/NepNewsBERT")
from transformers import pipeline
fill_mask = pipeline( "fill-mask", model=model, tokenizer=tokenizer, ) from pprint import pprint pprint(fill_mask(f"तिमीलाई कस्तो {tokenizer.mask_token}."))
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