Instructions to use harheem/bert-finetuned-ner-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harheem/bert-finetuned-ner-ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="harheem/bert-finetuned-ner-ko")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("harheem/bert-finetuned-ner-ko") model = AutoModelForTokenClassification.from_pretrained("harheem/bert-finetuned-ner-ko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from harheem/bert-finetuned-ner-ko: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/harheem/bert-finetuned-ner-ko/resolve/main/training_args.bin
- Command line
-
hf download hf://harheem/bert-finetuned-ner-ko/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/harheem/bert-finetuned-ner-ko/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 362a145c084abb4268254ec7960bf0fb7ef9aba618192d970efc3ca0b97fcf47
- Size of remote file:
- 4.98 kB
- SHA256:
- bf5e0c28f6cf3acf239646b55a5a06dbcfbe6b25fe9eae7e2142ec54c8af9681
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