Instructions to use denpa92/bert-base-cantonese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use denpa92/bert-base-cantonese with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("denpa92/bert-base-cantonese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from denpa92/bert-base-cantonese: direct link, hf CLI and curl.
- Browser
- Download file 409 MB
-
https://huggingface.co/denpa92/bert-base-cantonese/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://denpa92/bert-base-cantonese/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/denpa92/bert-base-cantonese/resolve/main/flax_model.msgpack
409 MB
- Xet hash:
- c3dce7c546f675b04db1cf2157be7daefcfeb41fe80cc9af1341ccc6df3df0f2
- Size of remote file:
- 409 MB
- SHA256:
- d145a129ca59c20a449502af58313c85fc17d123a8b5e075eaca6bdb21b61d4f
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