hqq-quantization
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.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install orchestra-research-ai-research-skills-hqq
Repository
Skill path: 10-optimization/hqq
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.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, DevOps, Data / AI.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: Orchestra-Research.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install hqq-quantization into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/Orchestra-Research/AI-Research-SKILLs before adding hqq-quantization to shared team environments
- Use hqq-quantization for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.