Instructions to use ChangeIsKey/change-type-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChangeIsKey/change-type-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ChangeIsKey/change-type-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ChangeIsKey/change-type-classifier") model = AutoModelForSequenceClassification.from_pretrained("ChangeIsKey/change-type-classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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# Cross-Encoder for Word
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This model
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The model can be used to detect
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The training code
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<b> Citation </b>
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output:
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url: "cfn.svg"
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# Cross-Encoder for Word-Sense Relationship Classification
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This model has been trained on word sense relations extracted from WordNet.
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The model can be used to detect what kind of relationships (among homonymy, antonymy, hypernonymy, hyponymy, and co-hyponymy) occur between word senses: Given a pair of word sense definitions, predict the sense relationship (homonymy, antonymy, hypernonymy, hyponymy, and co-hyponymy).
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The training code can be found here: [https://github.com/ChangeIsKey/change-type-classification](https://github.com/ChangeIsKey/change-type-classification)
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<b> Citation </b>
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