Instructions to use hfl/chinese-bert-wwm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-bert-wwm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-bert-wwm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-bert-wwm") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-bert-wwm") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dff85b861794d06ac52037e8356db8d10ff4fd6656918bf5ee0703d1c57df8ba
- Size of remote file:
- 409 MB
- SHA256:
- 7ffe8ddfdc3e647a8d3bcef8461230046446e000c013e683d0d175ea84b100a9
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