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:
- 0faf594670cf25d73f2706f9fa4495652575b0be8014525716dd4d3320ae7e92
- Size of remote file:
- 3.52 kB
- SHA256:
- 080d54c612f2804c9e7ef35a0052815f0c23031fcc73ab08c1a2c84ad3b218cd
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