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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ea3ae3a63c16ebc8b5eaf372e53539c29d4962df0abcb54d095be6b92b6c8a0
- Size of remote file:
- 409 MB
- SHA256:
- 729cf040302dd17067fe5c7ab1d0ebb8bafc2875242ee2d8df0e36768236c2f7
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