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Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
hqq-quantization is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # HQQ - Half-Quadratic Quantization Fast, calibration-free weight quantization supporting 8/4/3/2/1-bit precision with multiple optimized backends. ## When to u. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding hqq-quantization to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install Orchestra-Research/AI-Research-SKILLsReview the upstream source before running this command.
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# HQQ - Half-Quadratic Quantization Fast, calibration-free weight quantization supporting 8/4/3/2/1-bit precision with multiple optimized backends. ## When to use HQQ **Use HQQ whe