diff --git a/README.md b/README.md
index a17f744..64ffebd 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,8 @@
# ComfyUI-ZImageDit
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## 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.
+
´´