Instructions to use flax-community/Sinhala-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/Sinhala-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/Sinhala-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("flax-community/Sinhala-roberta") model = AutoModel.from_pretrained("flax-community/Sinhala-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from flax-community/Sinhala-roberta: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/flax-community/Sinhala-roberta/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://flax-community/Sinhala-roberta/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/flax-community/Sinhala-roberta/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- a3414340303df9577322146d83b98664ba19b93b479e65953acafd63dc46f2bb
- Size of remote file:
- 499 MB
- SHA256:
- 9f60d9a4d00f40acca726f6a1d6fded78d118b76b24837710624fba2a76417f9
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