Instructions to use JeremyFeng/machine-generated-text-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremyFeng/machine-generated-text-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremyFeng/machine-generated-text-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremyFeng/machine-generated-text-detection") model = AutoModelForSequenceClassification.from_pretrained("JeremyFeng/machine-generated-text-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49d922aa8d90e419654b4c7cd3b89371b6b062814f2cf18e619111f7100f60b8
- Size of remote file:
- 409 MB
- SHA256:
- 87c19c1e781725fba95601b80d719141baa58c2004540137f882209eed6cd948
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