BaohaoLiao / ApiQLinks
[EMNLP 2024] Quantize LLM to extremely low-bit, and finetune the quantized LLMs
☆13Updated 11 months ago
Alternatives and similar repositories for ApiQ
Users that are interested in ApiQ are comparing it to the libraries listed below
Sorting:
- Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks☆36Updated 5 months ago
- Unofficial implementations of block/layer-wise pruning methods for LLMs.☆72Updated last year
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆74Updated 8 months ago
- [ICML24] Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs☆89Updated 7 months ago
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆65Updated last year
- ☆26Updated 8 months ago
- The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".☆71Updated 3 months ago
- Official Implementation of FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective Propagation☆21Updated last month
- HALO: Hadamard-Assisted Low-Precision Optimization and Training method for finetuning LLMs. 🚀 The official implementation of https://arx…☆17Updated 5 months ago
- ☆10Updated 10 months ago
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆64Updated 3 months ago
- D^2-MoE: Delta Decompression for MoE-based LLMs Compression☆61Updated 3 months ago
- ☆136Updated 5 months ago
- SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference☆50Updated 7 months ago
- [ICLR 2024 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"☆86Updated 3 weeks ago
- [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models☆94Updated last year
- ☆18Updated 7 months ago
- LLM Inference with Microscaling Format☆24Updated 8 months ago
- ☆22Updated 8 months ago
- This repository contains the training code of ParetoQ introduced in our work "ParetoQ Scaling Laws in Extremely Low-bit LLM Quantization"☆87Updated last month
- [CoLM'25] The official implementation of the paper <MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression>☆139Updated this week
- AFPQ code implementation☆22Updated last year
- [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference☆43Updated last year
- ☆15Updated 8 months ago
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆36Updated 9 months ago
- An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization☆142Updated last month
- Work in progress.☆70Updated 2 weeks ago
- ☆24Updated 2 months ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆41Updated last year
- [ICML 2025] SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models☆34Updated 11 months ago