Instructions to use hfl/chinese-pert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/chinese-pert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hfl/chinese-pert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hfl/chinese-pert-base") model = AutoModel.from_pretrained("hfl/chinese-pert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d6a6f0f347487660ba8526f5c6740145305fae72e6148dad400c657a3660234
- Size of remote file:
- 412 MB
- SHA256:
- 114af50c2e4d7ef1263fd136e318839a661955d6fccd57141ccefbd534f5fd97
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