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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: [](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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``` |
