Text Classification
Transformers
PyTorch
Safetensors
English
roberta
mgt-detection
ai-detection
text-embeddings-inference
Instructions to use andreas122001/roberta-mixed-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreas122001/roberta-mixed-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="andreas122001/roberta-mixed-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("andreas122001/roberta-mixed-detector") model = AutoModelForSequenceClassification.from_pretrained("andreas122001/roberta-mixed-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccdcd630765de840cd3e433597dee9a446fe6bfc13f236dda67a6337a5828635
- Size of remote file:
- 997 MB
- SHA256:
- cf3b1c9a1b4ae2ae04940a3d45196bcd5e7d0b84bdd8750d35868b56c2c0b87f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.