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
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "do_basic_tokenize": true, "never_split": null, "name_or_path": "shibing624/macbert4csc-base-chinese", "special_tokens_map_file": "cache\\5559a99a8a2784cef7bf4784ffdb8f0ec2df952f0ca49d9aa3c7f46530fbc8ef.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "tokenizer_class": "BertTokenizer"} |