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 pytorch_model.bin 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/pytorch_model.bin
- Command line
-
hf download hf://flax-community/Sinhala-roberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/flax-community/Sinhala-roberta/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- ceeae263d0a3f31651c4b175611fb0246e1236972da008a77375e65208862a31
- Size of remote file:
- 499 MB
- SHA256:
- 0ae1d1d3c2f00db285c5d8f3175bf3ba9d8dab8af351d8f41462124f144e8be9
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