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GeezerVison is showing github.com β€” DefTruth - Overview

@DefTruth DefTruth Follow
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@DefTruth
DefTruth
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🎯
#pragma unroll

DefTruth DefTruth

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AI Infra Engineer @vipshop, Owner @xlite-dev, Prev @PaddlePaddleπŸ€–
2.1k followers Β· 188 following
  • @xlite-dev, @vipshop
  • Guangzhou, China
  • 01:39 (UTC +08:00)
  • https://deftruth.github.io

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Achievement: Pull Sharkx4Achievement: Starstruckx4Achievement: Pair Extraordinairex4Achievement: YOLOAchievement: Quickdraw

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@vipshop @xlite-dev
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DefTruth/README.md
πŸ€—πŸŽ‰ Hi! I'm DefTruth, an AI Infra Engineer (DiT / LLM). I built xlite-dev, Cache-DiT, ffpa-attn, LeetCUDA, lite.ai.toolkit, lihang-notes, torchlm, Awesome-LLM-Inference, Awesome-DiT-Inference | πŸŽ―πŸ¦… I also contributed to FastDeploy, SGLang , SGLang-Diffusion , vLLM , vLLM-Omni , Diffusers , GCMP | πŸšͺ🐍 I also built some open-source books at πŸ“– LeetCUDA, πŸ“– lihang-notes.

github follow ηŸ₯乎 pages DefTruth | Trendshift xlite-dev%2FLeetCUDA | Trendshift

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  1. xlite-dev/LeetCUDA xlite-dev/LeetCUDA Public

    An Open-source book with Modern CUDA learning Notes for Beginners - BF16/FP8/FP4, HGEMM, CuTe, Flash-Attention, etc.

    TeX 12.2k 1.3k

  2. xlite-dev/lite.ai.toolkit xlite-dev/lite.ai.toolkit Public

    A lite C++ AI toolkit: 100+ models with MNN, ORT and TRT, including Det, Seg, Stable-Diffusion, Face-Fusion.

    C++ 4.4k 784

  3. PaddlePaddle/FastDeploy PaddlePaddle/FastDeploy Public

    High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle

    Python 3.7k 757

  4. sgl-project/sglang sgl-project/sglang Public

    SGLang is a high-performance serving framework for large language models and multimodal models.

    Python 38.8k 10.4k

  5. vipshop/cache-dit vipshop/cache-dit Public

    A PyTorch-native inference engine with cache, parallelism, quantization and cpu offload for 100+ DiTs.

    Python 1.3k 94

  6. vipshop/ffpa-attn vipshop/ffpa-attn Public

    Kernel Library for Large Headdim Attention (64~1024, BF16/FP8/FP4), 1.5x~15x↑ vs PyTorch SDPA.

    Python 348 29

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