Instructions to use Developer9215/klue-ner-koelectra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Developer9215/klue-ner-koelectra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Developer9215/klue-ner-koelectra")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Developer9215/klue-ner-koelectra") model = AutoModelForTokenClassification.from_pretrained("Developer9215/klue-ner-koelectra", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Developer9215/klue-ner-koelectra: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/Developer9215/klue-ner-koelectra/resolve/main/training_args.bin
- Command line
-
hf download hf://Developer9215/klue-ner-koelectra/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Developer9215/klue-ner-koelectra/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 6b190067582f51a89c0e56323d4b85bfce7642733ea4810a9ea15f1344fa3bca
- Size of remote file:
- 5.37 kB
- SHA256:
- ffd2e32a7fc2aeb8f657379c1d824d0bfecc51ddb7772c67ce2e68a580490a7c
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