Instructions to use prosa-text/indobert-nusa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prosa-text/indobert-nusa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="prosa-text/indobert-nusa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("prosa-text/indobert-nusa") model = AutoModelForMaskedLM.from_pretrained("prosa-text/indobert-nusa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa3b72fcdd09992812e19903cd78ec4a260bb633cfe1c3f9e94e86fa035ef8a0
- Size of remote file:
- 1.34 GB
- SHA256:
- 76b96f733918c43e9596b290cf75f66fe86dd7fa0d2ecaba76b0beaed204705d
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