Instructions to use keshan/sinhala-roberta-mc4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keshan/sinhala-roberta-mc4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="keshan/sinhala-roberta-mc4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("keshan/sinhala-roberta-mc4") model = AutoModelForMaskedLM.from_pretrained("keshan/sinhala-roberta-mc4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from keshan/sinhala-roberta-mc4: direct link, hf CLI and curl.
- Browser
- Download file 1.68 MB
-
https://huggingface.co/keshan/sinhala-roberta-mc4/resolve/main/tokenizer.json
- Command line
-
hf download hf://keshan/sinhala-roberta-mc4/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/keshan/sinhala-roberta-mc4/resolve/main/tokenizer.json
1.68 MB
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