VITA-Group / LiGOLinks
[ICLR 2023] "Learning to Grow Pretrained Models for Efficient Transformer Training" by Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogerio Feris, David Cox, Zhangyang Wang, Yoon Kim
☆92Updated last year
Alternatives and similar repositories for LiGO
Users that are interested in LiGO are comparing it to the libraries listed below
Sorting:
- Code accompanying the paper "Massive Activations in Large Language Models"☆184Updated last year
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆55Updated 2 years ago
- ☆140Updated last year
- ☆105Updated last year
- Repository of the paper "Accelerating Transformer Inference for Translation via Parallel Decoding"☆120Updated last year
- [ICLR‘24 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"☆97Updated 4 months ago
- ☆30Updated 2 years ago
- Sparse Backpropagation for Mixture-of-Expert Training☆29Updated last year
- Code for "Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes"☆28Updated last year
- [NeurIPS-2024] 📈 Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies https://arxiv.org/abs/2407.13623☆89Updated last year
- ☆127Updated last year
- Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models☆142Updated 3 years ago
- ☆196Updated last year
- [ICML'24 Oral] The official code of "DiJiang: Efficient Large Language Models through Compact Kernelization", a novel DCT-based linear at…☆104Updated last year
- Some preliminary explorations of Mamba's context scaling.☆216Updated last year
- [EMNLP 2023, Main Conference] Sparse Low-rank Adaptation of Pre-trained Language Models☆83Updated last year
- The source code of "Merging Experts into One: Improving Computational Efficiency of Mixture of Experts (EMNLP 2023)":☆40Updated last year
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆67Updated last year
- [NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning☆31Updated 2 years ago
- This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).☆46Updated 3 years ago
- Official implementation of "DoRA: Weight-Decomposed Low-Rank Adaptation"☆124Updated last year
- Code for ICLR 2025 Paper "What is Wrong with Perplexity for Long-context Language Modeling?"☆103Updated 3 weeks ago
- Official PyTorch Implementation of EMoE: Unlocking Emergent Modularity in Large Language Models [main conference @ NAACL2024]☆35Updated last year
- ☆130Updated 3 years ago
- [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models☆106Updated last year
- Code for paper "Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning"☆83Updated last year
- Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)☆80Updated 2 years ago
- [ICLR2025] Codebase for "ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing", built on Megatron-LM.☆97Updated 10 months ago
- This is a repository for "PMET: Precise Model Editing in a Transformer"☆54Updated 2 years ago
- Language models scale reliably with over-training and on downstream tasks☆100Updated last year