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")# 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
- Xet hash:
- 45410e54e8ae9301019b81595d0366bbe5c2594a6798435f8d5df3f2e86df215
- Size of remote file:
- 595 MB
- SHA256:
- f69b13c3dcdbc56f426fe631080a64e22b96f11e14d7f2abc0b506c983e177cc
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