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
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README.md
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Input a noun phrase (NP) and the model will tag its syntactic head as
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Non-head tokens will be tagged as
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The model is intended to tag multiple heads in compound NPs. It is not
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intended to tag all heads in complex NPs.
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Input a noun phrase (NP) and the model will tag its syntactic head as HEAD.
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Non-head tokens will be tagged as NA.
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The model is intended to tag multiple heads in compound NPs. It is not
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intended to tag all heads in complex NPs.
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