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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da0af60ad7902cccfd165c641827de206d0fbbb3a87978f8c2a1c28b0fe398c9
- Size of remote file:
- 430 MB
- SHA256:
- 29a42aa5d63fe277d3bdba1a6180a83ce7bce87d507ab92829bcf2e53a370aa9
路
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