Text Classification
Transformers
Safetensors
English
modernbert
ai-detection
binary-classification
text-embeddings-inference
Instructions to use videogameaetoros/Ai_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use videogameaetoros/Ai_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="videogameaetoros/Ai_detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("videogameaetoros/Ai_detector") model = AutoModelForSequenceClassification.from_pretrained("videogameaetoros/Ai_detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
TutorCat AI Detector (ModernBERT)
Binary human vs AI text classifier for TutorCat integrity checks.
- Base:
answerdotai/ModernBERT-base - Labels:
0= human,1= ai - Train data:
integrity_human_ai_surface_v2_no_train.jsonl(~35k rows) - External holdout: accuracy 99.5%, AUROC 0.9999 (200 essays)
Load
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
repo = "videogameaetoros/Ai_detector"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForSequenceClassification.from_pretrained(repo)
model.eval()
text = "Your essay here..."
enc = tok(text, return_tensors="pt", truncation=True, max_length=384)
with torch.no_grad():
probs = torch.softmax(model(**enc).logits, dim=-1)[0]
print({"human": float(probs[0]), "ai": float(probs[1])})
Space
Used by https://huggingface.co/spaces/videogameaetoros/ai_detector via INTEGRITY_MODEL_REPO=videogameaetoros/Ai_detector.
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