Instructions to use cahya/bert-base-indonesian-522M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/bert-base-indonesian-522M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cahya/bert-base-indonesian-522M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cahya/bert-base-indonesian-522M") model = AutoModelForMaskedLM.from_pretrained("cahya/bert-base-indonesian-522M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84bb8ca72431931712dabe9369dd92904da3cab4cf522b051c235385a63b4f95
- Size of remote file:
- 445 MB
- SHA256:
- 1eb59077bebe9eaf97f5bd6b074286fdd514a404266b6b5a9e34bd44fa7732dc
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