SeeDream 4.5 Specialist 🎯
Specialist detector for SeeDream 4.5 (unfrozen last layer, 97-99% accuracy)
H100-Optimized Specialist Detector with Unfrozen Last Layer
Architecture
- Base: Vision Transformer (ViT-base-patch16-224)
- Layers 0-10: FROZEN (pretrained features)
- Layer 11: UNFROZEN (learns generator-specific patterns)
- Classifier: UNFROZEN (768 → 2)
- Trainable Parameters: ~100,000
- Training Data: 400 images (320 train / 40 val / 40 test)
Performance
| Metric | Score |
|---|---|
| Test Accuracy | 1.0000 (100.00%) |
| Precision | 1.0000 |
| Recall | 1.0000 |
| F1 Score | 1.0000 |
Features
✅ Specialist detector (trained only on SeeDream) ✅ Unfrozen last attention layer for generator-specific features ✅ Test-Time Augmentation (TTA) enabled ✅ Heavy regularization (prevents overfitting on small dataset) ✅ H100-optimized training
Usage
from transformers import ViTForImageClassification, ViTImageProcessor
from PIL import Image
import torch
model = ViTForImageClassification.from_pretrained("ash12321/seedream-4.5-specialist-h100")
processor = ViTImageProcessor.from_pretrained("google/vit-base-patch16-224")
image = Image.open("image.jpg")
inputs = processor(images=image, return_tensors="pt")
with torch.no_grad():
outputs = model(**inputs)
probs = torch.softmax(outputs.logits, dim=1)
if probs[0][1] > 0.5:
print(f"AI-Generated (SeeDream): {probs[0][1]:.2%}")
else:
print(f"Real: {probs[0][0]:.2%}")
Training Details
- Training Time: 2.1 minutes
- Best Epoch: 16
- Device: H100 GPU
- Unique data split (seed=456)
Limitations
⚠️ This is a specialist detector trained ONLY for SeeDream.
Does NOT detect:
- Other AI image generators
- General synthetic images
For comprehensive AI detection, use as part of an ensemble with other specialist detectors.