Alternatives and similar repositories for GradientFilter-CVPR23

Users that are interested in GradientFilter-CVPR23 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 months ago
• shawnricecake / search-llm
  [NeurIPS 2024] Search for Efficient LLMs
  ☆15Updated 9 months ago
• Hao840 / vanillaKD
  PyTorch code and checkpoints release for VanillaKD: https://arxiv.org/abs/2305.15781
  ☆76Updated last year
• Hao840 / manifold-distillation
  Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation. NeurIPS 2022.
  ☆32Updated 3 years ago
• MingSun-Tse / TPP
  [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)
  ☆33Updated 2 years ago
• VITA-Group / Random_Pruning
  [ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training by Shiwei Liu, Tianlo…
  ☆77Updated 2 years ago
• MingSun-Tse / Awesome-Efficient-ViT
  Recent Advances on Efficient Vision Transformers
  ☆54Updated 2 years ago
• lliai / DisWOT-CVPR2023
  ☆28Updated last year
• ylsung / ECoFLaP
  Code for "ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models" (ICLR 2024)
  ☆20Updated last year
• PeiyanFlying / SPViT
  ☆53Updated last year
• DefangChen / SimKD
  [CVPR-2022] Official implementation for "Knowledge Distillation with the Reused Teacher Classifier".
  ☆100Updated 3 years ago
• ModelTC / QLLM
  [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…
  ☆38Updated last year
• megvii-research / TPS-CVPR2023
  ☆47Updated 2 years ago
• andyrull / width-and-Depth-pruning-for-Vision-Transformer
  ☆19Updated 3 years ago
• xiusu / NAS-Bench-Macro
  NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021
  ☆37Updated 4 years ago
• OpenGVLab / LLMPrune-BESA
  BESA is a differentiable weight pruning technique for large language models.
  ☆17Updated last year
• lliai / EMQ-series
  [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization
  ☆28Updated last year
• orashi / NSE_NAS
  Official PyTorch implementation of "Evolving Search Space for Neural Architecture Search"
  ☆12Updated 4 years ago
• VITA-Group / M3ViT
  [NeurIPS 2022] “M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design”, Hanxue …
  ☆132Updated 2 years ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆31Updated 3 years ago
• YifanXu74 / Evo-ViT
  Official implement of Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer
  ☆73Updated 3 years ago
• theyoungkwon / TinyTrain
  The official implementation of TinyTrain [ICML '24]
  ☆22Updated last year
• IST-DASLab / spdy
  Code for ICML 2022 paper "SPDY: Accurate Pruning with Speedup Guarantees"
  ☆20Updated 2 years ago
• iamkanghyunchoi / ait
  It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher [CVPR 2022 Oral]
  ☆29Updated 3 years ago
• liuzechun / Data-Free-NAS
  Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV 2022.
  ☆32Updated 3 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
• MAC-AutoML / ITPruner
  ☆26Updated 3 years ago
• facebookresearch / NASViT
  code for NASViT
  ☆66Updated 3 years ago
• xjwu1024 / PPT
  The codebase for paper "PPT: Token Pruning and Pooling for Efficient Vision Transformer"
  ☆27Updated 11 months ago
• Jin-Ying / Multi-Level-Logit-Distillation
  Code for 'Multi-level Logit Distillation' (CVPR2023)
  ☆70Updated last year