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:
- baeee41aafadf61642ed4881699983cc98769eea958f362a3efd7dd91336167e
- Size of remote file:
- 443 MB
- SHA256:
- 2e2b3dc00e56b4aa04280bb6ed6cce99edf6e9c8c69a4a5765bbe337ecc6be72
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.