Instructions to use AryaSuprana/BRATA_RoBERTaBali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AryaSuprana/BRATA_RoBERTaBali with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AryaSuprana/BRATA_RoBERTaBali")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AryaSuprana/BRATA_RoBERTaBali") model = AutoModelForMaskedLM.from_pretrained("AryaSuprana/BRATA_RoBERTaBali", device_map="auto") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"datasets[1]" with value "Suara Saking Bali" is not valid. If possible, use a dataset id from https://hf.co/datasets.
BRATA (Basa Bali Used for Pretraining RoBERTa) is a pretrained language model trained using Basa Bali or Balinese Language with RoBERTa-base-uncased configuration. The datasets used for this pretraining were collected by extracting WikiBali or Wikipedia Basa Bali and some sources from Suara Saking Bali website. The pretrained language model trained using Google Colab Pro with Tesla P100-PCIE-16GB GPU. Pretraining process used 200 epoch and 2 batch size. The smallest training loss can be seen in Training metrics or Metrics tab.
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