Instructions to use hon9kon9ize/ModernCantoneseBert-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hon9kon9ize/ModernCantoneseBert-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hon9kon9ize/ModernCantoneseBert-Base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hon9kon9ize/ModernCantoneseBert-Base") model = AutoModelForMaskedLM.from_pretrained("hon9kon9ize/ModernCantoneseBert-Base") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- beb38ec2f5e88c187e6ef47aea65600b523d51ce228cdc6130f8381989848936
- Size of remote file:
- 7.26 MB
- SHA256:
- e702f87058eeab9c93fe564868dd72e9deb5e741efc16538f06fe534838fe03a
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