| # AGENTS.md — CommunityForensics-DeepfakeDet-ViT |
|
|
| ## What this repo is |
| Hugging Face model repo for `buildborderless/CommunityForensics-DeepfakeDet-ViT` — a ViT-Small classifier for deepfake image detection. Trained on 2.7M samples across 4,803 generators. This is a model distribution repo (no app, no build, no tests). |
|
|
| ## Key files |
| - **`model.safetensors`** — HF-format weights (Git LFS — ensure `git lfs pull` after clone) |
| - **`config.json`** — `ViTForImageClassification` config (384×384, 6 heads, num_labels=1, sigmoid output: real/fake) |
| - **`preprocessor_config.json`** — CLIP-style normalization, resize to shortest_edge=440, center-crop to 384 |
| - **`modeling_vit_classifier.py`** — **DEPRECATED** (moved to `scripts/`). Use standard HF path below. |
| - **`pretrained_weights/`** — original `.pt` checkpoints from training (also LFS) |
| - **`onnx/`** — 5 pre-exported ONNX variants (15MB–84MB) for CPU/GPU deployment. See README for variant guide. |
| |
| ## Usage |
| The model is hosted on Hugging Face. The standard way to load it is via `transformers`: |
| ```python |
| from transformers import ViTForImageClassification, ViTImageProcessor |
| model = ViTForImageClassification.from_pretrained("buildborderless/CommunityForensics-DeepfakeDet-ViT") |
| processor = ViTImageProcessor.from_pretrained("buildborderless/CommunityForensics-DeepfakeDet-ViT") |
| ``` |
| |
| The custom wrapper (`modeling_vit_classifier.py`) uses `timm.create_model` with a sigmoid output and `pretrained_weights/model_v11_ViT_384_base_ckpt.pt`. This is for standalone (non-HF-pipeline) inference requiring both `timm` and `transformers`. |
| |
| ## Dependencies |
| - `transformers >= 5.4.0` (required — older versions lack `shortest_edge` resize and will squash images) |
| - `timm` (for the deprecated ViTClassifier wrapper only) |
| - `torch`, `torchvision`, `Pillow` |
| - `onnxruntime >= 1.27` (for ONNX models) |
| |
| ## Scripts (in `scripts/`) |
| Data processing utilities for the eval dataset — not needed for inference: |
| - `convert_to_pytorch.py` — convert timm checkpoints to HuggingFace format |
| - `resample_evalset.py` — face-detection-based dataset filtering |
| - `restructure.py` — reorganize real/generated image directories |
| - `quick_analysis.py` — dataset statistics report |
| |
| ## Git LFS |
| All weight files (`.safetensors`, `.pt`, `.ckpt`, `.onnx`) are stored via Git LFS. Always run `git lfs pull` after cloning or the model files will be pointer stubs. The full ONNX model alone is 138MB — pull selectively with `git lfs pull --include="onnx/model_int8.onnx"` if you only need one variant. |
| |
| ## Remote |
| This repo is pushed to `https://huggingface.co/buildborderless/CommunityForensics-DeepfakeDet-ViT`, not GitHub. Standard `gh` CLI commands will not work. |
| |
