Instructions to use yihahn/ner_2006 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yihahn/ner_2006 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="yihahn/ner_2006")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("yihahn/ner_2006") model = AutoModelForTokenClassification.from_pretrained("yihahn/ner_2006", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yihahn/ner_2006: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/yihahn/ner_2006/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yihahn/ner_2006/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yihahn/ner_2006/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 903abd070fbdf0b924234af23bb7ca85e0dd185bfb49b9dd3bc9efa7e9d1b3e3
- Size of remote file:
- 433 MB
- SHA256:
- eff4d5ad92db7cae44be9236009eb8fe79fac7e473533abc381d9cf520b30f29
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