Create README.md
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README.md
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---
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language: "ISO 639-1 code for your language, or `multilingual`"
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thumbnail: "url to a thumbnail used in social sharing"
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tags:
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- array
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- of
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- tags
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license: "any valid license identifier"
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datasets:
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- array of dataset identifiers
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metrics:
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- array of metric identifiers
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widget:
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- text: "Plagiarism is the representation of another author's writing, thoughts, ideas, or expressions as one's own work."
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---
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# T5-large for Word Sense Disambiguation
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This is the checkpoint for T5-large after being trained on the Machine-Paraphrased Plagiarism Dataset: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3608000.svg)](https://doi.org/10.5281/zenodo.3608000)
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Additional information about this model:
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* [The longformer-base-4096 model page](https://huggingface.co/allenai/longformer-base-4096)
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* [Longformer: The Long-Document Transformer](https://arxiv.org/pdf/2004.05150.pdf)
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* [Official implementation by AllenAI](https://github.com/allenai/longformer)
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The model can be loaded to perform Plagiarism like so:
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```py
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from transformers import AutoModelForSequenceClassification, AutoTokenizer
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AutoModelForSequenceClassification("jpelhaw/longformer-base-plagiarism-detection")
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AutoTokenizer.from_pretrained("jpelhaw/longformer-base-plagiarism-detection")
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input = 'Plagiarism is the representation of another author's writing, thoughts, ideas, or expressions as one's own work.'
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example = tokenizer.tokenize(input, add_special_tokens=True)
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answer = model(**example)
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# "plagiarised"
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```
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