Instructions to use zypchn/berturk-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zypchn/berturk-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="zypchn/berturk-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("zypchn/berturk-ner") model = AutoModelForTokenClassification.from_pretrained("zypchn/berturk-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52e72b3cf01f3b5dfbd34865474f3068a2f5edaee266d97d44e33cd3b905b98e
- Size of remote file:
- 5.71 kB
- SHA256:
- e75f90fafd6ce8ba3ee1cfb2590186e61e2f8150e507da25f1e81e3687488eb4
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