Instructions to use hfl/chinese-macbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-macbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-macbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-macbert-base") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-macbert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cc722afaddc6c86e4a8c43f30bbf3230a7a5c2981b085e78c75933a9537a41e
- Size of remote file:
- 478 MB
- SHA256:
- 8ce3e21a00bfb22a1f0f93d232a2a0ed1ab29f2a077a847b1210785211294e9f
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