Alternatives and similar repositories for RegularizedBN

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

• BaohaoLiao / mefts
  [NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
  ☆33Updated 2 years ago
• roymiles / VeLoRA
  [NeurIPS 2024] VeLoRA : Memory Efficient Training using Rank-1 Sub-Token Projections
  ☆21Updated last year
• varunnair18 / FISH
  Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
  ☆59Updated 3 years ago
• VITA-Group / Random-MoE-as-Dropout
  [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…
  ☆56Updated 2 years ago
• sanagno / adaptively_sparse_attention
  ☆21Updated 2 years ago
• VITA-Group / Junk_DNA_Hypothesis
  [ICML 2024] Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity; Lu Yin*, Ajay Jaiswal*, Shiwei Liu, So…
  ☆16Updated 7 months ago
• JeanKaddour / NoTrainNoGain
  Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)
  ☆81Updated 2 years ago
• mlfoundations / patching
  Patching open-vocabulary models by interpolating weights
  ☆91Updated 2 years ago
• mlfoundations / clip_quality_not_quantity
  ☆29Updated 3 years ago
• changlin31 / AutoProg
  (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers
  ☆25Updated 8 months ago
• rgeirhos / dataset-pruning-metrics
  Metrics for "Beyond neural scaling laws: beating power law scaling via data pruning " (NeurIPS 2022 Outstanding Paper Award)
  ☆57Updated 2 years ago
• naotoo1 / Beyond-Neural-Scaling
  Implementation of Beyond Neural Scaling beating power laws for deep models and prototype-based models
  ☆34Updated 3 weeks ago
• HKUNLP / efficient-attention
  [EVA ICLR'23; LARA ICML'22] Efficient attention mechanisms via control variates, random features, and importance sampling
  ☆87Updated 2 years ago
• locuslab / massive-activations
  Code accompanying the paper "Massive Activations in Large Language Models"
  ☆186Updated last year
• shoaibahmed / llm_depth_pruning
  Official implementation of the paper: "A deeper look at depth pruning of LLMs"
  ☆15Updated last year
• mmatena / model_merging
  ☆79Updated 3 years ago
• berlino / gated_linear_attention
  ☆105Updated last year
• dydjw9 / Efficient_SAM
  ☆58Updated 2 years ago
• mlpen / YOSO
  ☆21Updated 4 years ago
• dguo98 / DiffPruning
  Parameter Efficient Transfer Learning with Diff Pruning
  ☆74Updated 4 years ago
• zju-vipa / training_free_model_merging
  This repository is the implementation of the paper Training Free Pretrained Model Merging (CVPR2024).
  ☆32Updated last year
• yikangshen / MoA
  Mixture of Attention Heads
  ☆51Updated 3 years ago
• locuslab / T-MARS
  Code for T-MARS data filtering
  ☆35Updated 2 years ago
• LukasHedegaard / structured-pruning-adapters
  Structured Pruning Adapters in PyTorch
  ☆19Updated 2 years ago
• song-wx / SIFT
  [ICML2024 Spotlight] Fine-Tuning Pre-trained Large Language Models Sparsely
  ☆23Updated 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 2 months ago
• uiuctml / MergeBench
  [NeurIPS 2025] MergeBench: A Benchmark for Merging Domain-Specialized LLMs
  ☆35Updated 2 months ago
• TencentARC / pi-Tuning
  Official code for "pi-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation", ICML 2023.
  ☆33Updated 2 years ago
• OpenNLPLab / Transnormer
  [EMNLP 2022] Official implementation of Transnormer in our EMNLP 2022 paper - The Devil in Linear Transformer
  ☆63Updated 2 years ago
• RobertCsordas / linear_layer_as_attention
  The official repository for our paper "The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns …
  ☆16Updated 5 months ago