Instructions to use hfl/chinese-roberta-wwm-ext-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-roberta-wwm-ext-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/chinese-roberta-wwm-ext-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-roberta-wwm-ext-large") model = AutoModelForMaskedLM.from_pretrained("hfl/chinese-roberta-wwm-ext-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90031861aed430d34364c0823a88831d3978a3502ca3bec2d6b2f6d1ba9e38b4
- Size of remote file:
- 1.31 GB
- SHA256:
- 4ac62d49144d770c5ca9a5d1d3039c4995665a080febe63198189857c6bd11cd
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