Update README.md

Author: DefTruth

README.md

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 - [2025-06-16]: **[🤗cache-dit](https://github.com/vipshop/cache-dit)** is released! A **Training-free** and **Easy-to-use** Cache Acceleration Toolbox for DiTs (**DBCache**, **DBPrune**, **TaylorSeer**, **FBCache**, **Cache CFG**, etc)🔥. Feel free to take a try!
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-- [2025-01-08]: [📚Split Q + Fully QKV Fine-grained Tiling](#mma-tiling-qkv) has been refactored into 🤖[ffpa-attn](https://github.com/xlite-dev/ffpa-attn.git): 📚FFPA - Yet another Faster Flash Prefill Attention with O(1)🎉SRAM complexity for headdim > 256, **1.8x~3x**🎉faster than SDPA EA: [📈L20 ~1.9x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-l20), [📈 A30 ~1.8x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-a30), [📈3080 ~2.9x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-3080), [📈4090 ~2.1x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-4090).
+- [2025-01-08]: **[🤖ffpa-attn](https://github.com/xlite-dev/ffpa-attn.git)** is released! Yet another Faster Flash Prefill Attention with O(1)🎉SRAM complexity for large headdim, **1.8x~3x↑**🎉 vs SDPA EA: [📈L20 ~1.9x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-l20), [📈A30 ~1.8x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-a30),[📈4090 ~2.1x↑🎉](https://github.com/xlite-dev/ffpa-attn?tab=readme-ov-file#L1-bench-4090).
 
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 - [2024-12-02]: HGEMM MMA kernels has been refactored into 🤖[HGEMM](https://github.com/xlite-dev/HGEMM.git): ⚡️Write HGEMM from scratch using Tensor Cores with WMMA, MMA and CuTe API, achieve peak⚡️ performance.
 
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 ## 📖 Contents
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