Instructions to use hon9kon9ize/bert-large-cantonese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hon9kon9ize/bert-large-cantonese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hon9kon9ize/bert-large-cantonese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hon9kon9ize/bert-large-cantonese") model = AutoModelForMaskedLM.from_pretrained("hon9kon9ize/bert-large-cantonese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04660f1b77d890cc430850f80f6d19d4dcb03553372ed6f7da2ee8381f7cac29
- Size of remote file:
- 1.3 GB
- SHA256:
- f97c429f280d9f3fad776eced37e9f41f6e191894033bf27b3c6e4e194be63cb
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