Instructions to use oya163/NepBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oya163/NepBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="oya163/NepBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("oya163/NepBERT") model = AutoModel.from_pretrained("oya163/NepBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
upload flax model
48e21e7 -
allow flax
c996d99
-
Update config.json
60e2eea
-
Update config.json
4542bed
-
Update config.json
8474b3c -
Update special_tokens_map.json
0ee046f -
Update tokenizer_config.json
247a5c6 -
Update training_args.bin
91dd639 -
Update merges.txt
4712ebc -
Update pytorch_model.bin
df38196 -
Update vocab.json
b16afaf -
initial commit
c3bce6c