Instructions to use keshan/sinhala-roberta-oscar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keshan/sinhala-roberta-oscar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="keshan/sinhala-roberta-oscar")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("keshan/sinhala-roberta-oscar") model = AutoModelForMaskedLM.from_pretrained("keshan/sinhala-roberta-oscar") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e91aac392ecc3d33595ddbde1c7c10fef0a6faaca941bb6db15eeeb9662a8e5e
- Size of remote file:
- 499 MB
- SHA256:
- e691367614a80c7e81d952031c95683122a7ddf5e09be494aec09c6836e234f7
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