Instructions to use joon09/kor-naver-ner-name-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joon09/kor-naver-ner-name-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="joon09/kor-naver-ner-name-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("joon09/kor-naver-ner-name-v2") model = AutoModelForTokenClassification.from_pretrained("joon09/kor-naver-ner-name-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from joon09/kor-naver-ner-name-v2: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/joon09/kor-naver-ner-name-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://joon09/kor-naver-ner-name-v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/joon09/kor-naver-ner-name-v2/resolve/main/pytorch_model.bin
471 MB
- Xet hash:
- 9ec115d6cc19dbfa42a124a9f394def51411a19d7d45c0bd1372989eeb135e84
- Size of remote file:
- 471 MB
- SHA256:
- 390f86b80f2d938ef0fcaf4786235346f3a541c1b0b6c203ecc9753d2c0e9769
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