Instructions to use acul3/Roberta-Large-Indo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acul3/Roberta-Large-Indo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="acul3/Roberta-Large-Indo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("acul3/Roberta-Large-Indo") model = AutoModelForMaskedLM.from_pretrained("acul3/Roberta-Large-Indo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from acul3/Roberta-Large-Indo: direct link, hf CLI and curl.
- Browser
- Download file 2.13 MB
-
https://huggingface.co/acul3/Roberta-Large-Indo/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
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hf download hf://acul3/Roberta-Large-Indo@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/acul3/Roberta-Large-Indo/resolve/refs%2Fpr%2F1/tokenizer.json
2.13 MB
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