Text Classification
Transformers
PyTorch
English
roberta
generated_text_detection
llm_content_detection
AI_detection
Instructions to use SuperAnnotate/roberta-large-llm-content-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SuperAnnotate/roberta-large-llm-content-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SuperAnnotate/roberta-large-llm-content-detector")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SuperAnnotate/roberta-large-llm-content-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eee1befae1f38823a84832d573272a2f03f53e7ce95b6a22f799d51a15f0486f
- Size of remote file:
- 1.42 GB
- SHA256:
- 4f9dc942be6d845c0a7e862d10c4c52f3c6b81eb20b47c16c4bb99f04c302b92
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