Rebels Krea-2 GGUFs

KREA-2 GGUF Weights Quantized GGUF weights for the Krea-2 Base model, optimized for low-VRAM and consumer hardware local workflows via ComfyUI. GGUF MODEL FILES: https://huggingface.co/realrebelai/KREA-2_GGUFs/tree/main 🚀 Overview Krea-2 is a Diffusion Transformer (DiT). Standard GGUF custom nodes will throw an Unexpected architecture type error natively. To run these weights, you must use our patched custom node fork. 📥 Downloading and Installation 1. Custom Node Requirements (Mandatory) Standard loaders do not yet recognize krea2 architecture tags in GGUF metadata. Clone the following custom node into your ComfyUI/custom_nodes/ directory: Repository: RealRebelAI/ComfyUI-GGUF_KREA-2 2. Required Support Models Place these base model files in your standard ComfyUI models/ directory: Text Encoder (CLIP): Qwen3-VL-4B-FP8-Scaled.safetensors (Load via CLIPLoader , ensuring Type is set to krea2 ) VAE: qwen_image_vae.safetensors (Load via VAELoader ) 3. GGUF Weight Installation Download your preferred quantization file (e.g., Krea-2-Base-Q4_K_S.gguf ) from the Files and versions tab of this repository. Place the downloaded .gguf file into your ComfyUI/models/unet/ (or equivalent GGUF directory) folder. Load the model in ComfyUI using the UnetLoaderGGUF node. ⚙️ Workflow Notes Ensure your conditioning setup is mapped appropriately to handle the stacked hidden state requirements of multimodal DiTs to avoid latent sequence mismatch errors.