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