Instructions to use jpwahle/longformer-base-plagiarism-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpwahle/longformer-base-plagiarism-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jpwahle/longformer-base-plagiarism-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jpwahle/longformer-base-plagiarism-detection") model = AutoModelForSequenceClassification.from_pretrained("jpwahle/longformer-base-plagiarism-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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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 =
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example = tokenizer.tokenize(input, add_special_tokens=True)
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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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