Instructions to use Sakonii/distilbert-base-nepali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sakonii/distilbert-base-nepali with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Sakonii/distilbert-base-nepali")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Sakonii/distilbert-base-nepali") model = AutoModelForMaskedLM.from_pretrained("Sakonii/distilbert-base-nepali") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 069ed6ffd6ff63138a6fa32050f166d4435bbb8dc7d407d50830ae0aca540efa
- Size of remote file:
- 268 MB
- SHA256:
- 468c12085f0c4601324dafa3e7156c3699426cc3964263c4ee82b6bc43da219e
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