Instructions to use Shushant/nepaliBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shushant/nepaliBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Shushant/nepaliBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Shushant/nepaliBERT") model = AutoModelForMaskedLM.from_pretrained("Shushant/nepaliBERT") - Notebooks
- Google Colab
- Kaggle
Fix: Add newline to fix SyntaxError in example code
#4
by anon-repair-bot - opened
Description
The original example code triggers a SyntaxError due to a missing line break between two statements:
from pprint import pprint pprint(fill_mask(f"तिमीलाई कस्तो {tokenizer.mask_token}."))
Changes
Replaced:
from pprint import pprint pprint(fill_mask(...))
with:
from pprint import pprint
pprint(fill_mask(...))
Testing
The code has been successfully tested and runs without error.
Note
This contribution is part of an ongoing research initiative to systematically identify and correct faulty example code in Hugging Face Model Cards.
We would appreciate a timely review and integration of this patch to support code reliability and enhance reproducibility for downstream users.