AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
AIMET consolidated LLM topology analysis into a single entry point and expanded model support to cover Qwen2.5, Qwen3-VL, Phi-3.5/4, and Gemma variants. The week also focused on fixing encoding propagation issues during ONNX QDQ export, including validation of encodings before conversion,…
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Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in aimet's README, structure, and recent commits — answers won't invent code they haven't seen.
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Read head_dim and KV heads per layer for transformers 5.17 heterogeneous configs (#7921)
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.