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", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Shushant/nepaliBERT") model = AutoModelForMaskedLM.from_pretrained("Shushant/nepaliBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a3851dedbe0dfa75823b2d1795677f26c865db87dd8be5c259430a0615f0649
- Size of remote file:
- 438 MB
- SHA256:
- f8174d875adbce71ea22059f2594942a1f0eb44fb2b8491d6efcc1c41bd65a36
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