Instructions to use Sakonii/deberta-base-nepali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sakonii/deberta-base-nepali with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Sakonii/deberta-base-nepali")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Sakonii/deberta-base-nepali") model = AutoModelForMaskedLM.from_pretrained("Sakonii/deberta-base-nepali", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Sakonii/deberta-base-nepali: direct link, hf CLI and curl.
- Browser
- Download file 2.13 MB
-
https://huggingface.co/Sakonii/deberta-base-nepali/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sakonii/deberta-base-nepali/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sakonii/deberta-base-nepali/resolve/main/tokenizer.json
2.13 MB
File too large to display, you can check the raw version instead.