Text Classification
Transformers
Safetensors
English
multimodal
image-classification
distilbert
vit
gated-fusion
digital-humanities
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("xablex/prosody_models", device_map="auto")Quick Links
Prosody Page Classifiers
Three finetuned models for binary page classification in the
Princeton Prosody Archive corpus. Labels are
TU (0) and non-TU (1). Each subfolder is independently loadable
— use whichever modality you have inputs for.
| Folder | Model |
|---|---|
distilbert-text/ |
DistilBERT text classifier (text-only) |
vit-image/ |
ViT-base image classifier (image-only) |
gated-fusion/ |
Gated-fusion multimodal classifier (text + image) |
distilbert-text/andvit-image/are standard Hugging Face repos (AutoModelForSequenceClassification/AutoModelForImageClassification).gated-fusion/is a custom multimodal model; load it via the bundledmodeling_gatedfusion.py(see that folder's README).
See each subfolder's README.md for a copy-paste usage snippet.
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xablex/prosody_models")