Instructions to use Ransaka/SinhalaRoberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ransaka/SinhalaRoberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Ransaka/SinhalaRoberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Ransaka/SinhalaRoberta") model = AutoModelForMaskedLM.from_pretrained("Ransaka/SinhalaRoberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ebc75d45a292d8d338cc931571e8adc5bce0430c0a29351ead3a00b79cf1862
- Size of remote file:
- 273 MB
- SHA256:
- eafb6bba7732477545289c4ed341727710c7669931aa6cf161d45f50c05adffa
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