yuchaoli / PSTLinks
Source code for IJCAI 2022 Long paper: Parameter-Efficient Sparsity for Large Language Models Fine-Tuning.
☆15Updated 3 years ago
Alternatives and similar repositories for PST
Users that are interested in PST are comparing it to the libraries listed below
Sorting:
- BESA is a differentiable weight pruning technique for large language models.☆17Updated last year
- ☆59Updated last year
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆33Updated 11 months ago
- [ICLR 2025] Official implementation of paper "Dynamic Low-Rank Sparse Adaptation for Large Language Models".☆20Updated 4 months ago
- [ICLR 2022] "Unified Vision Transformer Compression" by Shixing Yu*, Tianlong Chen*, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Li…☆54Updated last year
- 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
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆57Updated last year
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆29Updated last year
- [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
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- Official implementation of the paper: "A deeper look at depth pruning of LLMs"☆15Updated last year
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆53Updated 2 years ago
- [KDD'22] Learned Token Pruning for Transformers☆98Updated 2 years ago
- [ICCV-2023] EMQ: Evolving Training-free Proxies for Automated Mixed Precision Quantization☆26Updated 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
- This project is the official implementation of our accepted ICLR 2022 paper BiBERT: Accurate Fully Binarized BERT.☆88Updated 2 years ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 3 years ago
- This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).☆46Updated 2 years ago
- ☆21Updated 9 months ago
- [NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang…☆89Updated last year
- Are gradient information useful for pruning of LLMs?☆46Updated last year
- A curated list of Early Exiting papers, benchmarks, and misc.☆117Updated last year
- Structured Pruning Adapters in PyTorch☆19Updated last year
- AFPQ code implementation☆22Updated last year
- ☆12Updated last year
- ☆25Updated 3 years ago
- Official PyTorch implementation of CD-MOE☆11Updated 4 months ago
- ☆29Updated last year
- Less is More: Task-aware Layer-wise Distillation for Language Model Compression (ICML2023)☆35Updated last year
- [ICLR 2022] "Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, and No Retraining" by Lu Miao*, Xiaolong Luo*, T…☆31Updated 3 years ago