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:
- e5600ffda93597be06367f4d9564cdb85f0c8f8bf7577eefd6dfe7a3823ad08a
- Size of remote file:
- 3.18 kB
- SHA256:
- c7b223e6fdf9c31644fd42d1521811a97c7c7062ee89a9ab685f0253e2b662ca
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