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:
- ff5e9db724c8c0e4fba5926c41b74b2733c46bcf493a643ebbc37af706fb58bb
- Size of remote file:
- 5.3 kB
- SHA256:
- 722042a2baa97175bb5f8a095306d4e83a7d40838ee77988210f0099c120c846
路
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