Alternatives and similar repositories for OWS

Users that are interested in OWS are comparing it to the libraries listed below

• osehmathias / lisa
  LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
  ☆36Updated last year
• SempraETY / Pruning-via-Merging
  ☆23Updated last year
• zyxxmu / DSnoT
  Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…
  ☆50Updated last year
• harveyhuang18 / EMR_Merging
  [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging
  ☆75Updated 10 months ago
• locuslab / massive-activations
  Code accompanying the paper "Massive Activations in Large Language Models"
  ☆195Updated last year
• mrflogs / LoRA-Pro
  Official code for our paper, "LoRA-Pro: Are Low-Rank Adapters Properly Optimized? "
  ☆143Updated 9 months ago
• aim-uofa / LoRAPrune
  ☆63Updated last year
• yule-BUAA / MergeLLM
  Codes for Merging Large Language Models
  ☆35Updated last year
• tanganke / weight-ensembling_MoE
  Code for paper "Merging Multi-Task Models via Weight-Ensembling Mixture of Experts"
  ☆30Updated last year
• ROIM1998 / APT
  [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
  ☆46Updated last year
• czg1225 / dParallel
  dParallel: Learnable Parallel Decoding for dLLMs
  ☆56Updated 3 months ago
• EnnengYang / AdaMerging
  AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.
  ☆100Updated last year
• horseee / CoT-Valve
  CoT-Valve: Length-Compressible Chain-of-Thought Tuning
  ☆89Updated 11 months ago
• GATECH-EIC / ACT
  [ICML 2024] Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibrati…
  ☆46Updated last year
• hahnyuan / ASVD4LLM
  Activation-aware Singular Value Decomposition for Compressing Large Language Models
  ☆84Updated last year
• TsinghuaC3I / SoRA
  [EMNLP 2023, Main Conference] Sparse Low-rank Adaptation of Pre-trained Language Models
  ☆84Updated last year
• DavidFanzz / SCMoE
  ☆28Updated last year
• Lucky-Lance / Expert_Sparsity
  [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models
  ☆113Updated last year
• haiquanlu / AlphaPruning
  [NeurIPS 2024] AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
  ☆31Updated 7 months ago
• Chongjie-Si / Subspace-Tuning
  A generalized framework for subspace tuning methods in parameter efficient fine-tuning.
  ☆168Updated 7 months ago
• Lucky-Lance / SPP
  [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
  ☆21Updated last year
• sail-sg / Attention-Sink
  [ICLR 2025] When Attention Sink Emerges in Language Models: An Empirical View (Spotlight)
  ☆152Updated 6 months ago
• TUDB-Labs / MoE-PEFT
  An Efficient LLM Fine-Tuning Factory Optimized for MoE PEFT
  ☆131Updated 10 months ago
• ycjing / Awesome-Model-Merging
  A curated list of Model Merging methods.
  ☆96Updated last month
• GeniusHTX / TALE
  ☆144Updated 4 months ago
• lliai / Awesome-Low-Rank-Adaptation
  Awesome-Low-Rank-Adaptation
  ☆126Updated last year
• htqin / IR-QLoRA
  [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…
  ☆67Updated last year
• bethgelab / sober-reasoning
  A Sober Look at Language Model Reasoning
  ☆92Updated 2 months ago
• UNITES-Lab / MC-SMoE
  [ICLR‘24 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"
  ☆103Updated 7 months ago
• hemingkx / TokenSkip
  [EMNLP 2025] TokenSkip: Controllable Chain-of-Thought Compression in LLMs
  ☆200Updated last month