Alternatives and similar repositories for pMoE_CNN

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

• shawnricecake / search-llm
  [NeurIPS 2024] Search for Efficient LLMs
  ☆15Updated 8 months ago
• OpenGVLab / LLMPrune-BESA
  BESA is a differentiable weight pruning technique for large language models.
  ☆17Updated last year
• Daner-Wang / VTC-LFC
  ☆27Updated 2 years ago
• lliai / DisWOT-CVPR2023
  ☆28Updated last year
• wzhuang-xmu / LoSA
  [ICLR 2025] Official implementation of paper "Dynamic Low-Rank Sparse Adaptation for Large Language Models".
  ☆23Updated 6 months ago
• leo-yangli / VB-LoRA
  This repo contains the source code for VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks (NeurIPS 2024).
  ☆42Updated 11 months ago
• ylsung / ECoFLaP
  Code for "ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models" (ICLR 2024)
  ☆20Updated last year
• megvii-research / TPS-CVPR2023
  ☆47Updated 2 years ago
• OpenGVLab / DiffRate
  [ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging tech…
  ☆101Updated 2 years ago
• ModelTC / QLLM
  [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…
  ☆39Updated last year
• MingSun-Tse / Why-the-State-of-Pruning-so-Confusing
  [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…
  ☆40Updated last month
• ModelTC / L2_Compression
  ☆13Updated last year
• scale-lab / MTLoRA
  The official implementation for MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learning (CVPR '24)
  ☆66Updated 3 months ago
• sdc17 / CrossGET
  [ICML 2024] CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers
  ☆34Updated 9 months ago
• 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
• waltonfuture / MM-UPT
  [NeurIPS 2025] Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPO
  ☆50Updated 3 weeks ago
• 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
• Lucky-Lance / SPP
  [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
  ☆21Updated last year
• MPSC-UMBC / Efficient-Vision-Language-Models-A-Survey
  [2025] Efficient Vision Language Models: A Survey
  ☆32Updated 2 months ago
• haiquanlu / AlphaPruning
  [NeurIPS 2024] AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
  ☆27Updated 4 months ago
• ROIM1998 / APT
  [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
  ☆45Updated last year
• UMass-Embodied-AGI / Mod-Squad
  ☆92Updated 2 years ago
• zysxmu / DFSQ
  super-resolution; post-training quantization; model compression
  ☆13Updated last year
• xjwu1024 / PPT
  The codebase for paper "PPT: Token Pruning and Pooling for Efficient Vision Transformer"
  ☆26Updated 10 months ago
• NVlabs / SMCP
  ☆22Updated 2 years ago
• iboing / CorDA
  CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for task-aware parameter-efficient fine-tuning(NeurIPS 2024)
  ☆52Updated 8 months ago
• sdc17 / UPop
  [ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers
  ☆105Updated 9 months ago
• GATECH-EIC / Castling-ViT
  [CVPR 2023] Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference
  ☆30Updated last year
• NUS-HPC-AI-Lab / Dynamic-Tuning
  The official implementation of "2024NeurIPS Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation"
  ☆48Updated 9 months ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆33Updated 2 years ago