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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.

Translated[Three Years of Interviews, Five Years of Mock Interviews] An interview resource platform for AIGC/LLM/AI Agent algorithm engineers. It covers practical interview and written-test experience and core, cross-cycle knowledge for the AI industry, including AIGC, LLM large models, AI Agents, embodied intelligence, traditional deep learning, computer vision, natural language processing, autonomous driving, machine learning, reinforcement learning, big data mining, world models, the metaverse, AGI, and more.