Alternatives and similar repositories for LLMPrune-BESA:

Users that are interested in LLMPrune-BESA are comparing it to the libraries listed below

• 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 2 years ago
• ziplab / QLLM
  [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…
  ☆27Updated last year
• shawnricecake / search-llm
  [NeurIPS 2024] Search for Efficient LLMs
  ☆13Updated 3 months ago
• ModelTC / QLLM
  [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…
  ☆36Updated 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…
  ☆47Updated last year
• VITA-Group / BackRazor_Neurips22
  [Neurips 2022] “ Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropogation”, Ziyu Jiang*, Xuxi Chen*, Xueqin Huan…
  ☆19Updated 2 years ago
• HuangOwen / QAT-ACS
  [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"
  ☆30Updated 8 months ago
• NVlabs / SMCP
  ☆21Updated 2 years ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆33Updated last year
• Lucky-Lance / SPP
  [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
  ☆20Updated 11 months ago
• ylsung / ECoFLaP
  Code for "ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models" (ICLR 2024)
  ☆19Updated last year
• imagination-research / LCSC
  [ICLR 2025] Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
  ☆14Updated 2 months ago
• yxli2123 / LoSparse
  ☆51Updated last year
• LukasHedegaard / structured-pruning-adapters
  Structured Pruning Adapters in PyTorch
  ☆17Updated last year
• VILA-Lab / GBLM-Pruner
  Are gradient information useful for pruning of LLMs?
  ☆43Updated last year
• ggjy / vision_weak_to_strong
  ☆38Updated last year
• chenjoya / dropit
  DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training (ICLR 2023)
  ☆30Updated 2 years ago
• OpenGVLab / DiffAgent
  [CVPR 2024] DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language Model
  ☆17Updated last year
• zju-vipa / training_free_model_merging
  This repository is the implementation of the paper Training Free Pretrained Model Merging (CVPR2024).
  ☆29Updated last year
• ruikangliu / Quantized-Reasoning-Models
  Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"
  ☆30Updated last week
• ModelTC / L2_Compression
  ☆13Updated 10 months ago
• htqin / DSG
  This project is the official implementation of our accepted IEEE TPAMI paper Diverse Sample Generation: Pushing the Limit of Data-free Qu…
  ☆14Updated 2 years ago
• ROIM1998 / APT
  [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
  ☆39Updated 11 months ago
• iamkanghyunchoi / ait
  It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]
  ☆29Updated 2 years ago
• GATECH-EIC / Linearized-LLM
  [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
  ☆30Updated 10 months ago
• Daner-Wang / VTC-LFC
  ☆26Updated 2 years ago
• alexandertheus / Intra-Fusion
  Towards Meta-Pruning via Optimal Transport, ICLR 2024 (Spotlight)
  ☆16Updated 5 months ago
• hikvision-research / SAViT
  ☆12Updated last year
• GATECH-EIC / ShiftAddViT
  [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
  ☆32Updated last year
• shoaibahmed / llm_depth_pruning
  Official implementation of the paper: "A deeper look at depth pruning of LLMs"
  ☆15Updated 9 months ago