Instructions to use ckiplab/bert-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ckiplab/bert-base-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ckiplab/bert-base-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ckiplab/bert-base-chinese") model = AutoModelForMaskedLM.from_pretrained("ckiplab/bert-base-chinese", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fae1e861ad368a2d2845ed432b1b9bb1bd422c36822d5e62aa4e8a7717c2e08
- Size of remote file:
- 409 MB
- SHA256:
- c8f9ef93f8cdd38195915be80c329ed246f8e6243ca82a54fb345ecb4edd459c
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