Instructions to use svjack/JBert_Zh_Condition_Extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use svjack/JBert_Zh_Condition_Extractor with Transformers:
# Load model directly from transformers import AutoTokenizer, JointBERT tokenizer = AutoTokenizer.from_pretrained("svjack/JBert_Zh_Condition_Extractor") model = JointBERT.from_pretrained("svjack/JBert_Zh_Condition_Extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 939ca0ae2169f3300d251c26ef904aed3da1f848068b9df9f28c5304e9c14cf8
- Size of remote file:
- 409 MB
- SHA256:
- e10832f8692f2622540764252237663ba32d6587d5a8c9af42adfe7e7ae9182c
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