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README2.md

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+# SageAttention 2.2.0 — Pre-built Wheel
+
+Pre-compiled SageAttention 2.2.0 wheel for **Linux x86_64** with CUDA 13 and C++20.
+
+## Compatibility
+
+| Component | Version |
+|-----------|---------|
+| Python | 3.12 |
+| PyTorch | 2.15.0 nightly (cu132) |
+| CUDA Toolkit | 13.3 |
+| GPU | Ada Lovelace (sm_89) — RTX 4050/4060/4070/4080/4090 |
+| SageAttention | 2.2.0 |
+
+## Install
+
+```bash
+pip install sageattention-2.2.0-cp312-cp312-linux_x86_64.whl --no-deps
+```
+
+## Build from Source (if needed)
+
+### Requirements
+- CUDA Toolkit (nvcc)
+- PyTorch with CUDA support
+- 16GB+ RAM or adequate swap
+
+### Steps
+
+```bash
+git clone --depth 1 https://github.com/thu-ml/SageAttention.git /tmp/SageAttention
+cd /tmp/SageAttention
+
+# Patch: PyTorch 2.15 nightly requires C++20
+sed -i 's/-std=c++17/-std=c++20/g' setup.py
+
+# Build
+CUDA_HOME=/usr/local/cuda-13.3 \
+TORCH_CUDA_ARCH_LIST="8.9" \
+MAX_JOBS=1 \
+NVCC_APPEND_FLAGS="--threads 8" \
+python setup.py install
+```
+
+### Create Wheel
+
+```bash
+python setup.py bdist_wheel
+cp dist/*.whl /path/to/wheels/
+```
+
+## Notes
+
+- Built on Ubuntu 24.04 with 14GB RAM + 19GB swap
+- `MAX_JOBS=1` used to avoid OOM during CUDA kernel compilation
+- PyTorch 2.15 nightly requires C++20; upstream SageAttention ships with C++17 which must be patched
+- Wheel includes sm_80 (Ampere) and sm_89 (Ada) kernels