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:
- 3fb51cc010717843de091e604d9fbf8d724947db356ce2e3e89f4d55b3fe0fe7
- Size of remote file:
- 15.7 MB
- SHA256:
- b710c5b4491cfbb9f2430f519c66bafe687cd0ad592bee2a21266f3834e2688f
路
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