Instructions to use 9pinus/macbert-base-chinese-medicine-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 9pinus/macbert-base-chinese-medicine-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="9pinus/macbert-base-chinese-medicine-recognition")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("9pinus/macbert-base-chinese-medicine-recognition") model = AutoModelForTokenClassification.from_pretrained("9pinus/macbert-base-chinese-medicine-recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0050bc53ea48ae7cd899a23681eb6b11e94b7f325ed590a79cdcdcca94a1c55
- Size of remote file:
- 407 MB
- SHA256:
- ea880e5f75542569dfb660af06f3eb72ef098830654c022daaeef8ece3dc1dca
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