Instructions to use NlpHUST/bert-base-vn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NlpHUST/bert-base-vn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NlpHUST/bert-base-vn")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NlpHUST/bert-base-vn") model = AutoModelForMaskedLM.from_pretrained("NlpHUST/bert-base-vn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1db87d266adc36f0fc2585f40e10d342c80d8b3dafeeb71fbbd2a9514d795d1
- Size of remote file:
- 535 MB
- SHA256:
- a446473a63c05b2d727a7bbdab0b590c2fc0f7ec03a67a6c1acbe02a2bd0d6c4
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