Update README.md

README.md

@@ -8,14 +8,14 @@ As title, lot of third party librarys which are important for running NN lack pr
 
 ***Use At Your Own Risks, Check Official Release To See if There Are Any Official Supports On Your HW Regularly***
 
-**Inlcuded Library**
+### Inlcuded Library
 * Flash Attention
 * Xformers (with cutlass/flash attention built-in)
 * NATTEN
 * SageAttention
 * vLLM
 
-***IMPORTANT NOTE:***
+### IMPORTANT NOTE
 1. I only ensure those wheels can works on RTX50 series (sm120) GPUs, if your platform is mixed with different sm/cu arch GPUs, you may still need to compile them by yourself
 2. Env
     * Pytorch: 2.7.0
@@ -25,4 +25,10 @@ As title, lot of third party librarys which are important for running NN lack pr
     * Tested platform: Ubuntu 22.04 and 24.04
     * CPU arch: amd64 (x86-64)
 3. Not all the wheels are fully functional (due to deps things or source implementation), for example, cutlass w8a8 scaled mm is not working in vllm, you need to use `VLLM_TEST_FORCE_FP8_MARLIN=1` to make VLLM works normally with fp8 weight quantization. If you are using flash attention, you need `VLLM_FLASH_ATTN_VERSION=2` to make it work on 5090
-4. If you meet any problem or need wheels for specific setup you can open discussion, but I can't ensure I will do it or not.
+4. If you meet any problem or need wheels for specific setup you can open discussion, but I can't ensure I will do it or not.
+
+### Tips
+* Install `triton==3.3.1` for better RTX50 series support
+* Install `nvidia-nccl-cu12==2.26.5` for correct multi-gpu deps for RTX50 series
+  * Torch 2.7.0 use 2.26.2 in their requirements which is not compatibile with RTX50 series, you should install this from pypi directly with `pip isntall nvidia-nccl-cu12>2.26.2`
+* I build all those wheel with `python -m build -n -w .` which is more suitable in modern python packaging, I recommend all the user who want to compile those wheel by themselves follow this scheme. (No matter the project use pyproject or setup.py, build package will works)