Instructions to use frett/chinese_extract_longbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_longbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_longbert", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_longbert", trust_remote_code=True) model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_longbert", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2cad251059adc3eb8d43dcc3d99ca04049e907f6b188844c69d34440df17b26
- Size of remote file:
- 5.24 kB
- SHA256:
- 9b6eb71d5d8040476b860432bbcca50838baa225a6bab4496ce7359b31657105
路
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