Instructions to use aplycaebous/VAC-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aplycaebous/VAC-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="aplycaebous/VAC-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("aplycaebous/VAC-BERT") model = AutoModelForMaskedLM.from_pretrained("aplycaebous/VAC-BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53814fc08b4fdde30e668981d924c7b9beaad0f0a1c8033f4de8d8f70f5422c7
- Size of remote file:
- 64.3 MB
- SHA256:
- b75c937c758bf6e1c3b4e44e459e8dfbe545fe6aec529748adf10465c17e20bd
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