update README with Q8 info.

README.md

@@ -18,7 +18,7 @@ pipeline_tag: text-to-image
 
 This repository hosts the **Z-Image Turbo Control Unified V2** model. This is a specialized architecture that unifies the powerful **Z-Image Turbo** base transformer with enhanced **ControlNet** capabilities into a single, cohesive model. This unified pipeline supports multiple generation modes in one place: **Text-to-Image, Image-to-Image, ControlNet, and Inpainting**.
 
-Unlike traditional pipelines where ControlNet is an external add-on, this model integrates control layers directly into the transformer structure. This enables **Unified GGUF Quantization**, allowing the entire merged architecture (Base + Control) to be quantized (e.g., Q4_K_M) and run efficiently on consumer hardware with limited VRAM. This version also introduces significant optimizations, architectural improvements, and bug fixes for features like `group_offload`.
+Unlike traditional pipelines where ControlNet is an external add-on, this model integrates control layers directly into the transformer structure. This enables **Unified GGUF Quantization**, allowing the entire merged architecture (Base + Control) to be quantized (e.g., Q4_K_M, Q8_0) and run efficiently on consumer hardware with limited VRAM. This version also introduces significant optimizations, architectural improvements, and bug fixes for features like `group_offload`.
 
 ## 📥 Installation
 
@@ -43,7 +43,8 @@ pip install -r requirements.txt
 
 ## 📂 Repository Structure
 
-*   `./transformer/z_image_turbo_control_unified_v2.1_q4_k_m.gguf`: The unified, quantized model weights.
+*   `./transformer/z_image_turbo_control_unified_v2.1_q4_k_m.gguf`: The unified, quantized Q4_K_M model weights.
+*   `./transformer/z_image_turbo_control_unified_v2.1_q8_0.gguf`: The unified, quantized Q8_0 model weights.
 *   `infer_controlnet.py`: Script for running controlnet inference.
 *   `infer_inpaint.py`: Script for running inpaint inference.
 *   `infer_t2i.py`: Script for running text-to-image inference.