Instructions to use RJ3vans/SSCCVspanTagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJ3vans/SSCCVspanTagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RJ3vans/SSCCVspanTagger")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RJ3vans/SSCCVspanTagger") model = AutoModelForTokenClassification.from_pretrained("RJ3vans/SSCCVspanTagger") - Notebooks
- Google Colab
- Kaggle
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The model should tag the tokens in the sentence with information about whether or not they are contained within particular types of syntactic constituents. If you find the model useful, please cite my thesis which presents the dataset used for finetuning:
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Evans, R. (2020) Sentence Simplification for Text Processing. Doctoral thesis. University of Wolverhampton. Wolverhampton, UK. (
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There you will find more information about the tagging scheme.
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The model should tag the tokens in the sentence with information about whether or not they are contained within particular types of syntactic constituents. If you find the model useful, please cite my thesis which presents the dataset used for finetuning:
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Evans, R. (2020) Sentence Simplification for Text Processing. Doctoral thesis. University of Wolverhampton. Wolverhampton, UK. (https://rj3vans.github.io/Evans2020_SentenceSimplificationForTextProcessing.pdf)
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There you will find more information about the tagging scheme.
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