Instructions to use frett/chinese_extract_pert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_pert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_pert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_pert") model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_pert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13f960fee7b04fb3fe7c7500ee9362a8529d5abb265e8764d1e493489b4ec8a7
- Size of remote file:
- 5.24 kB
- SHA256:
- aef8b9587d6114babaac0860abcf331be1765e67f91371df22c2cb02e35acc1a
路
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