# Prosody ViT Image Classifier

Fine-tuned `google/vit-base-patch16-224` for binary page classification in the
[Princeton Prosody Archive](https://prosody.princeton.edu/) corpus, using the
scanned page **image** only.

- **Classes:** `TU` (0), `non-TU` (1)
- **Architecture:** `ViTForImageClassification` (HF-native)

```python
from transformers import AutoModelForImageClassification, AutoImageProcessor
from PIL import Image
import torch

model = AutoModelForImageClassification.from_pretrained("./vit-image")
proc  = AutoImageProcessor.from_pretrained("./vit-image")

img = Image.open("page.png").convert("RGB")
inp = proc(img, return_tensors="pt")
with torch.no_grad():
    probs = model(**inp).logits.softmax(-1)[0]
print({model.config.id2label[i]: float(p) for i, p in enumerate(probs)})
```