awq-quantization
Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.
| Field | Value |
|---|---|
| Owner | Orchestra-Research |
| Curator | Thomas Cherickal |
| Source | Orchestra-Research/AI-Research-SKILLs |
| Repo stars | 14,542 |
| License | MIT |
| Repo last push | 2026-10-11 |
Links
- Roles: local-ai-engineer
- Source repo: Orchestra-Research/AI-Research-SKILLs
- Same repo: axolotl, deepspeed, distributed-llm-pretraining-torchtitan, fine-tuning-openvla-oft, fine-tuning-serving-openpi, gguf-quantization, gptq, hqq-quantization
- Registry seed skills for this role: local-ai-engineer seed skills