Text Classification
Transformers
Safetensors
English
distilbert
ai-text-detection
academic-integrity
paperguard
text-embeddings-inference
Instructions to use vediumsameer/paperguard-ai-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vediumsameer/paperguard-ai-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vediumsameer/paperguard-ai-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vediumsameer/paperguard-ai-detector") model = AutoModelForSequenceClassification.from_pretrained("vediumsameer/paperguard-ai-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update model card to v2.0 (calibrated logit margin; base = distilbert-base-cased)
Verified signaturec59bd84
-
Upload v2.0 Mega-Dataset model (eval_loss=0.0003)
Verified signature385f41c -
Upload README.md with huggingface_hub
Verified signature2165388 -
Upload multi-dataset trained v1.5 AI detection model (99.81% Acc)
Verified signature55dcf38 -
Upload README.md with huggingface_hub
Verified signaturea259b0a -
Upload folder using huggingface_hub
Verified signature3609884 -
initial commit
Verified signature60a9c59