Model Details
Full Model IDbuildborderless/CommunityForensics-DeepfakeDet-ViT
Pipeline / Taskimage-classification
Librarytransformers
Downloads (all-time)797.3K
Likes12
Last Modified6/11/2025
Author / Orgbuildborderless
PrivateNo � public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-classification", model="buildborderless/CommunityForensics-DeepfakeDet-ViT")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerssafetensorsvitimage-classificationtimmdetectiondeepfakeforensicsdeepfake_detectioncommunityopensightarxiv:2411.04125base_model:timm/vit_small_patch16_384.augreg_in21k_ft_in1kbase_model:finetune:timm/vit_small_patch16_384.augreg_in21k_ft_in1klicense:mitendpoints_compatibleregion:us
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Open on Hugging Face →Browse Model Files ↗�� Browse All Models🖼�� Task: Image Classification
This model is designed for the Image Classification task. Explore more models for this use case.
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⬇ Downloads797.3K
����� Community Likes12
🛠�� Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.