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Strategies for LLM Evals (GuideLLM, lm-eval-harness, OpenAI Evals Workshop) — Taylor Jordan Smith

Strategies for LLM Evals (GuideLLM, lm-eval-harness, OpenAI Evals Workshop) — Taylor Jordan Smith

Traditional benchmarks and leaderboards are insufficient for production AI. This summary details a practical, multi-layered evaluation strategy, moving from foundational system performance to factual accuracy and finally to safety and bias, using open-source tools like GuideLLM, lm-eval-harness, and Promptfoo.

Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten

Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten

A deep dive into SGLang, an open-source serving framework for LLMs. This summary covers its core features, history, performance optimization techniques like CUDA Graph and Eagle 3 speculative decoding, and how to contribute to the project.

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