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 5.3 kB
-
https://huggingface.co/luohuashijieyoufengjun/ner_based_bert-base-chinese/resolve/c04138a12781bb25f934c5be09e078efa9a8fd06/training_args.bin
- Command line
-
hf download hf://luohuashijieyoufengjun/ner_based_bert-base-chinese@c04138a12781bb25f934c5be09e078efa9a8fd06/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/luohuashijieyoufengjun/ner_based_bert-base-chinese/resolve/c04138a12781bb25f934c5be09e078efa9a8fd06/training_args.bin
5.3 kB
- Xet hash:
- e31a0506d426e600daffdf14c694917f760b2927f4f868f85bef39f3e0691eea
- Size of remote file:
- 5.3 kB
- SHA256:
- 0c1d585d377bc9eabd6a90b33fcdea758fda45b757232dacfec5e72f9b417ecd
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