Instructions to use frett/chinese_extract_mac_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_mac_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_mac_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_mac_bert") model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_mac_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0240f6993173fde4db0925afeb3ceaeeceaebcd5c136f74968ec592a0c84157
- Size of remote file:
- 407 MB
- SHA256:
- 26a9de6ce89e20f354f8ef597e7ed402c7b59fe656ddabcae4d0ee8520dc51d1
路
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