📈 GitHub Trending1. NVIDIA/Model-OptimizerA unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.2. FxEmbed/FxEmbedFix X/Twitter and Bluesky embeds! Use multiple images, videos, polls, translations and more on Discord, Telegram and others3. julyx10/lapAn offline-first photo manager for large local libraries4. leejet/stable-diffusion.cppDiffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++

1. 

   Bboysoul的博客

   📈 GitHub Trending1. NVIDIA/Model-OptimizerA unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.2. FxEmbed/FxEmbedFix X/Twitter and Bluesky embeds! Use multiple images, videos, polls, translations and more on Discord, Telegram and others3. julyx10/lapAn offline-first photo manager for large local libraries4. leejet/stable-diffusion.cppDiffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++

   3小时前

   📈 GitHub Trending
   
   1. NVIDIA/Model-Optimizer
   A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
   
   2. FxEmbed/FxEmbed
   Fix X/Twitter and Bluesky embeds! Use multiple images, videos, polls, translations and more on Discord, Telegram and others
   
   3. julyx10/lap
   An offline-first photo manager for large local libraries
   
   4. leejet/stable-diffusion.cpp
   Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference in pure C/C++

   3小时前