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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- add0ceb35a94cccaeeb3d954a9fa2b215d5f2ec237e5eced76fda07896f819b0
- Size of remote file:
- 545 MB
- SHA256:
- c92573edd91f26270dd0b24a042cd4fcd654e940dc8983d77807fefd0f70bb08
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