GitHub / ksm26 / Efficiently-Serving-LLMs

Learn the ins and outs of efficiently serving Large Language Models (LLMs). Dive into optimization techniques, including KV caching and Low Rank Adapters (LoRA), and gain hands-on experience with Predibase’s LoRAX framework inference server.

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Topics: batch-processing, deep-learning-techniques, inference-optimization, large-scale-deployment, machine-learning-operations, model-acceleration, model-inference-service, model-serving, optimization-techniques, performance-enhancement, scalability-strategies, server-optimization, serving-infrastructure, text-generation

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