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ForgeryVCR-Team
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ForgeryVCR

Image-Text-to-Text
Transformers
Safetensors
image-forensics
image-manipulation-detection
visual-tool-use
qwen3-vl
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Gated model: Login with a HF token with gated access permission
hf auth login
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="ForgeryVCR-Team/ForgeryVCR")
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ForgeryVCR-Team/ForgeryVCR", device_map="auto")
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ForgeryVCR

ForgeryVCR is a visual-centric image-forensics agent built on Qwen3-VL-4B-Instruct. It actively calls ELA, FFT, NPP, and Zoom-In tools, classifies an image as authentic or tampered, and localizes manipulated regions with bounding boxes.

The released merged GRPO checkpoint is stored under GRPO/.

Download 

hf download youqiwong/ForgeryVCR \
  --repo-type model \
  --include "GRPO/*" \
  --local-dir weights/ForgeryVCR

Use the checkpoint from the ForgeryVCR repository:

INFERENCE_MODEL_PATH=weights/ForgeryVCR/GRPO \
INFERENCE_DATASETS="all" \
bash scripts/run_inference.sh

The full tool definitions, prompts, preprocessing, SAM2 mask generation, and evaluation code are maintained in the project repository.

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