This is a repository accompanying the survey Edge AI Meets LLM (coming soon), containing a comprehensive list of papers, codebases, toolchains, and open-source frameworks. It is intended to serve as a handbook for researchers and developers interested in Edge/Mobile LLMs.
Optimized Qwen2.5-3B using GPTQ, reducing size from 5.75GB → 1.93GB and improving inference speed. Ideal for efficient edge AI deployments.
Run your decisions through a jury of 12 AI minds before you commit.
An open-source, edge-native clinical AI evaluation framework designed to benchmark Large Language Models against NASA's Autonomous Crew Healthcare System (ACHS) standards and spaceflight hazards.
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