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")# pip install -U transformers accelerate # 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
Download training_args.bin from prosa-text/indobert-nusa: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/prosa-text/indobert-nusa/resolve/main/training_args.bin
- Command line
-
hf download hf://prosa-text/indobert-nusa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prosa-text/indobert-nusa/resolve/main/training_args.bin
4.47 kB
- Xet hash:
- 45f6a58a7c86c77adf8d259619ca2d314554e682ad025fc2a1b1765bfc8de749
- Size of remote file:
- 4.47 kB
- SHA256:
- 99b5ce78b785f68e7248ffd1816ea037d3b2028f0ac090be1f2f2b9c0bcdaa52
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