base_model:

• prithivMLmods/VideoGuard-Qwen3.5-4B-Safety-RL-Uncensored library_name: transformers tags:
• text-generation-inference
• llama-cpp
• reinforcement-learning
• video-text-to-text
• alignment-training
• RLHF
• RFT
• video-understanding
• video-classification
• video-safety
• content-safety
• content-moderation
• safety-classifier
• guardrail datasets:
• prithivMLmods/OpenVideo-Scene-Reasoning
• PALM-Lab/vid-guard-rlhf-unsafe license: apache-2.0 language:
• en pipeline_tag: video-text-to-text

VideoGuard-Qwen3.5-4B-Safety-RL-Uncensored-GGUF

VideoGuard-Qwen3.5-4B-Safety-RL-Uncensored is a multimodal safety classifier built on top of Qwen/Qwen3.5-4B. The model was trained on a mixture of approximately 10,000 video safety and scene-reasoning samples to analyze video content and classify potentially unsafe content across predefined safety categories. The model is designed to generate a structured DESCRIPTION, EXPLANATION, and GUARDRAIL output, making it suitable for video content filtering, safety evaluation, and multimodal guardrail research.

[!NOTE] This model is an experimental release and may generate unexpected classifications or reasoning artifacts in certain scenarios. Safety classifications should be treated as model predictions rather than definitive judgments.

Model Files

llama.cpp

LLM inference in C/C++ — https://github.com/ggml-org/llama.cpp