Instructions to use hfl/chinese-bert-wwm-ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-bert-wwm-ext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-bert-wwm-ext")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-bert-wwm-ext") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-bert-wwm-ext", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0bffb90be522964adaa9378d8a7b1d2be746003dda9584da7f3f78ff69675d7
- Size of remote file:
- 412 MB
- SHA256:
- 713b8d2e12ef4004e6a8efec1779b6424c20cd1b84f583fe6ea91121b5511336
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