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:
- 8f9b045a4340d80f11ec985b441ad8542d745afd480ec3753d406a2662e0a781
- Size of remote file:
- 430 MB
- SHA256:
- a09ee7199d00164648e34c2ff242af9b5dee3ae2a30c9e0ac2457e08ea7ea2b7
路
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