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
Update README.md
Browse files
README.md
CHANGED
|
@@ -46,7 +46,8 @@ from transformers import AutoModelForSequenceClassification, AutoTokenizer
|
|
| 46 |
AutoModelForSequenceClassification("jpelhaw/longformer-base-plagiarism-detection")
|
| 47 |
AutoTokenizer.from_pretrained("jpelhaw/longformer-base-plagiarism-detection")
|
| 48 |
|
| 49 |
-
input = "Plagiarism is the representation of another author's writing,
|
|
|
|
| 50 |
|
| 51 |
|
| 52 |
example = tokenizer.tokenize(input, add_special_tokens=True)
|
|
|
|
| 46 |
AutoModelForSequenceClassification("jpelhaw/longformer-base-plagiarism-detection")
|
| 47 |
AutoTokenizer.from_pretrained("jpelhaw/longformer-base-plagiarism-detection")
|
| 48 |
|
| 49 |
+
input = "Plagiarism is the representation of another author's writing, \
|
| 50 |
+
thoughts, ideas, or expressions as one's own work."
|
| 51 |
|
| 52 |
|
| 53 |
example = tokenizer.tokenize(input, add_special_tokens=True)
|