Instructions to use Ayaka/bart-base-cantonese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ayaka/bart-base-cantonese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Ayaka/bart-base-cantonese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Ayaka/bart-base-cantonese") model = AutoModel.from_pretrained("Ayaka/bart-base-cantonese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download embed_params.dat from Ayaka/bart-base-cantonese: direct link, hf CLI and curl.
- Browser
- Download file 38.9 MB
-
https://huggingface.co/Ayaka/bart-base-cantonese/resolve/main/embed_params.dat
- Command line
-
hf download hf://Ayaka/bart-base-cantonese/embed_params.dat
-
curl -L -o embed_params.dat https://huggingface.co/Ayaka/bart-base-cantonese/resolve/main/embed_params.dat
38.9 MB
- Xet hash:
- 10a2b8861e0ab6bc3ba3ff3cb90d0e4b375df112aaaa75d4dbc3b928348bf66e
- Size of remote file:
- 38.9 MB
- SHA256:
- 895650afebc771eafd848dc9703ee8292c5b9fa6d77a409d2d1b66059c69a67a
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