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:
- 973400fee4491e21fd687f0e1faf26fa09cacb8966a2577a1ca07fc963452e61
- Size of remote file:
- 409 MB
- SHA256:
- 547f69b1949b290945708c825e7ffa81da1b7e5ece8031ff9c7a179c422237d8
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