Instructions to use luohuashijieyoufengjun/ner_based_bert-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luohuashijieyoufengjun/ner_based_bert-base-chinese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="luohuashijieyoufengjun/ner_based_bert-base-chinese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("luohuashijieyoufengjun/ner_based_bert-base-chinese") model = AutoModelForTokenClassification.from_pretrained("luohuashijieyoufengjun/ner_based_bert-base-chinese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from luohuashijieyoufengjun/ner_based_bert-base-chinese: direct link, hf CLI and curl.
- Browser
- Download file 5.71 kB
-
https://huggingface.co/luohuashijieyoufengjun/ner_based_bert-base-chinese/resolve/main/training_args.bin
- Command line
-
hf download hf://luohuashijieyoufengjun/ner_based_bert-base-chinese/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/luohuashijieyoufengjun/ner_based_bert-base-chinese/resolve/main/training_args.bin
5.71 kB
- Xet hash:
- c929be866aa1146bc0674adb42cf83e7e27aa08b0123daff423a682494f176a5
- Size of remote file:
- 5.71 kB
- SHA256:
- 5ffb872709eec0a95eed970df3306e01b69a36c60a206ad08474daa9f15187a7
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