Instructions to use RJ3vans/NPheadTagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJ3vans/NPheadTagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RJ3vans/NPheadTagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RJ3vans/NPheadTagger") model = AutoModelForTokenClassification.from_pretrained("RJ3vans/NPheadTagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1de99f27f4c9e86bc76f15c536f6cd81decb5d467827c4ac8ecde2cab772873
- Size of remote file:
- 1.33 GB
- SHA256:
- 203d73af66a924289ee42e6882d7c0519e9ff73f72a4f80f024392bc5ae86b98
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