Instructions to use junnyu/bert_chinese_mc_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junnyu/bert_chinese_mc_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="junnyu/bert_chinese_mc_base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("junnyu/bert_chinese_mc_base") model = AutoModelForMaskedLM.from_pretrained("junnyu/bert_chinese_mc_base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb487eaef409593bfcb8147bc2b90d77eb1c8ebf979b77de1d65dcea651e425f
- Size of remote file:
- 409 MB
- SHA256:
- a4d4f73c6e1c0c8d79601d328357d568d85b9a88bd0db6f59418a6b5ceb7f8e5
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