Instructions to use hfl/chinese-roberta-wwm-ext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-roberta-wwm-ext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-roberta-wwm-ext")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-roberta-wwm-ext") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-roberta-wwm-ext") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d76fa70460ac54454cb49e1dda06b33a1e57a83a8da1a1b669ace9ec00193b0b
- Size of remote file:
- 412 MB
- SHA256:
- 1ded5a5a1c7841dee6e47942f7b5bf2bcf6f73ff19197580f852f7f638f86b35
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