Instructions to use frett/chinese_extract_bert_scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_bert_scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_bert_scratch")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_bert_scratch") model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_bert_scratch") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09ed63e30a22976fe4f8e5137f62a19cd4826917bb24deda9f977bc3232b4ce6
- Size of remote file:
- 407 MB
- SHA256:
- b86949662c648ba720e4aa0392d2658d2d7db486100ac56e0a715b7c4fc07b62
路
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