Alternatives and similar repositories for task_singular_vectors

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

• harveyhuang18 / EMR_Merging
  [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging
  ☆62Updated 5 months ago
• EnnengYang / AdaMerging
  AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.
  ☆88Updated 9 months ago
• nik-dim / tall_masks
  Official repository of "Localizing Task Information for Improved Model Merging and Compression" [ICML 2024]
  ☆47Updated 9 months ago
• tanganke / peta
  Code for paper "Parameter Efficient Multi-task Model Fusion with Partial Linearization"
  ☆21Updated 10 months ago
• lliai / LoRA-Zoo
  Awesome-Low-Rank-Adaptation
  ☆115Updated 9 months ago
• iboing / CorDA
  CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for task-aware parameter-efficient fine-tuning(NeurIPS 2024)
  ☆48Updated 6 months ago
• tanganke / weight-ensembling_MoE
  Code for paper "Merging Multi-Task Models via Weight-Ensembling Mixture of Experts"
  ☆29Updated last year
• EnnengYang / RepresentationSurgery
  Representation Surgery for Multi-Task Model Merging. ICML, 2024.
  ☆46Updated 10 months ago
• NUS-HPC-AI-Lab / DD-Ranking
  Data distillation benchmark
  ☆67Updated last month
• TsinghuaC3I / SoRA
  [EMNLP 2023, Main Conference] Sparse Low-rank Adaptation of Pre-trained Language Models
  ☆81Updated last year
• ROIM1998 / APT
  [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
  ☆44Updated last year
• haiquanlu / AlphaPruning
  [NeurIPS 2024] AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models
  ☆25Updated 2 months ago
• ycjing / Awesome-Model-Merging
  A curated list of Model Merging methods.
  ☆92Updated 10 months ago
• Pbihao / SLM
  ☆28Updated last year
• NUS-HPC-AI-Lab / DATM
  ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
  ☆102Updated last year
• pixeli99 / OWS
  Official Pytorch Implementation of "Outlier-weighed Layerwise Sampling for LLM Fine-tuning" by Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei …
  ☆34Updated 2 months ago
• sdc17 / CrossGET
  [ICML 2024] CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.
  ☆34Updated 7 months ago
• zefang-liu / AdaMoLE
  AdaMoLE: Adaptive Mixture of LoRA Experts
  ☆34Updated 9 months ago
• GATECH-EIC / ACT
  [ICML 2024] Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibrati…
  ☆40Updated last year
• tanganke / opcm
  ☆14Updated 6 months ago
• princetonvisualai / icons
  ☆20Updated 3 months ago
• yule-BUAA / MergeLLM
  Codes for Merging Large Language Models
  ☆33Updated 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…
  ☆49Updated last year
• r-three / smear
  ☆30Updated last year
• DavidFanzz / SCMoE
  ☆26Updated last year
• duguodong7 / pcb-merging
  [NeurIPS 2024] For paper Parameter Competition Balancing for Model Merging
  ☆45Updated 10 months ago
• eric-ai-lab / PEViT
  Official implementation of AAAI 2023 paper "Parameter-efficient Model Adaptation for Vision Transformers"
  ☆105Updated 2 years ago
• LINs-lab / DynMoE
  [ICLR 2025] Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
  ☆121Updated last month
• shaoshitong / EDC
  Elucidated Dataset Condensation (NeurIPS 2024)
  ☆21Updated 10 months ago
• osehmathias / lisa
  LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
  ☆33Updated last year