Instructions to use Azion/bert-based-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azion/bert-based-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Azion/bert-based-chinese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Azion/bert-based-chinese") model = AutoModelForMaskedLM.from_pretrained("Azion/bert-based-chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81e4de349a9fd6468cb5f05a83d96d9830969c5f977455c6350fa4a516501162
- Size of remote file:
- 409 MB
- SHA256:
- 98521d7b74766009eebb36f5a7bd49ac6ab2ae581251039b3040e4895edcf6f4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.