Instructions to use ShinDC/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShinDC/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ShinDC/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ShinDC/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("ShinDC/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ShinDC/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/ShinDC/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://ShinDC/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ShinDC/bert-finetuned-ner/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 9beca7f23fdcc0cac948e1ad951a866ed529a36244a76f60849934611ac8ee43
- Size of remote file:
- 4.54 kB
- SHA256:
- b1fbfbd58200b1c4a7fbd3a8cca1faad6363e143489b2bd42e896579ee981979
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