Revise README with updated images and notes

Updated README.md with new image tags and installation instructions.

README.md

@@ -1,8 +1,8 @@
 # ComfyUI-ZImageDit
 
 
-<img width="1024" height="1024" alt="ComfyUI-zimage-diffusers-wrapper_00002_" src="https://github.com/user-attachments/assets/eac45a4d-ad75-4a0f-9de7-b6bcf51f2292" />
-<img width="2139" height="1075" alt="image" src="https://github.com/user-attachments/assets/bac94951-c82c-46f4-ab14-089875693072" />
+<img width="559"  alt="ComfyUI-zimage-diffusers-wrapper_00002_" src="https://github.com/user-attachments/assets/eac45a4d-ad75-4a0f-9de7-b6bcf51f2292" />
+<img width="559"  alt="image" src="https://github.com/user-attachments/assets/bac94951-c82c-46f4-ab14-089875693072" />
 
 
 ## What is this ?
@@ -21,21 +21,22 @@ Check these example LLM "Clones" , credits to the original authors (Civitai) for
 - **installation**
     you might have to install some pip packages manually, nothing too difficult
     at the hart you need: accelerate, the latest diffusers from source to support z-image pipeline
-    
-- **install_sdnq.bat** might help on windows because it looks like their toml file has an issue with license (open inside the bat and change paths)
-- for **flash attention** find a whl, I did not bother yet as it's ok-ish speedwise, if you need you can try these places:
+ 
+- **install_sdnq.bat** might help on windows because it looks like their toml file has an issue with double licensing (open inside the bat and change paths)
+- ** diffusers** to install the latest diffusers manually via git to support the pipeline **(from the embedded python folder if using portable comfyui)**:
+  `python.exe -m pip install git+https://github.com/huggingface/diffusers.git`
+- for **flash attention (optional) ** find a .whl, if you need you can try these places:
   - seems to be **the best place to find them**:
   -   https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.5.4
   - other places
     - prebuilt wheels https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/tag/v0.4.10 (i ended up using one package from here, it gives a nice speed boost, sage attention makes it slower, not sure why)
     - prebuilt wheels  https://huggingface.co/Kijai/PrecompiledWheels/tree/main
     - prebuilt wheels https://huggingface.co/lldacing/flash-attention-windows-wheel/tree/main
-- about **compile**: does not work (for me)
-- you **need to install the latest diffusers manually via git to support the pipeline** (from the embedded python folder):
-  `python.exe -m pip install git+https://github.com/huggingface/diffusers.git`
+- about **compile**: does not work, for me. 
+
 - **if startup fails** check requirements for what is needed (quanto is not needed for these nodes, but for the other broken ones)
 - **weights** are downloaded by diffusers on first run for sdnq nodes, in you huggingface default cache folder unless you change it
-- **some option dont work** or i did not finish porting, test.
+- **some option dont work** or I did not finish porting, test.
 - there are **other** files in the other folders but they are experimental, ignore them (you might need quanto even or other installs)
 - internally sampling happens with flowmatching euler
 - only tested on windows (but linux should be even easier)
@@ -57,7 +58,10 @@ Enrico aka ErosDiffusion
 
 ps.: you might have issues installing, but I have no time to support :D
 
-note: this does not use ComfyUI memory management, so use carefully. Ißve added an option to unload but did not test it not sure it works.
-the memory footprint is around 7gb vram more or less, you can safely run up to 2048x2048
+**additional notes**:
+- this does not use ComfyUI memory management, so use carefully.
+- I have added an option to unload but did not test it not sure it works.
+- the memory footprint is around 7gb vram more or less, you can safely run up to 2048x2048 i can run lmstudio with qwen4 3b in parallel and between ram and vram and this, and never get oom.
+  
 
 ´´