imagination-research / LCSCLinks
[ICLR 2025] Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
☆16Updated 9 months ago
Alternatives and similar repositories for LCSC
Users that are interested in LCSC are comparing it to the libraries listed below
Sorting:
- Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs☆21Updated 3 weeks ago
- BESA is a differentiable weight pruning technique for large language models.☆17Updated last year
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆39Updated last year
- [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models☆35Updated last year
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆50Updated last year
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆41Updated 3 months ago
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆67Updated last year
- [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models☆21Updated last year
- [ICML24] Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs☆96Updated last year
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆30Updated last year
- ☆62Updated 2 years ago
- [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"☆61Updated 5 months ago
- ☆27Updated 8 months ago
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆38Updated last year
- [ICLR 2025] Mixture Compressor for Mixture-of-Experts LLMs Gains More☆63Updated 9 months ago
- The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"☆68Updated 8 months ago
- [NeurIPS 2024] Search for Efficient LLMs☆15Updated 10 months ago
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆35Updated last year
- [NeurIPS 2023] ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer☆30Updated 2 years ago
- Official Code For Dual Grained Quantization: Efficient Fine-Grained Quantization for LLM☆14Updated last year
- [ICLR 2025] Official implementation of paper "Dynamic Low-Rank Sparse Adaptation for Large Language Models".☆23Updated 8 months ago
- ☆30Updated last year
- ☆24Updated last year
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆82Updated last year
- ☆10Updated last year
- torch_quantizer is a out-of-box quantization tool for PyTorch models on CUDA backend, specially optimized for Diffusion Models.☆22Updated last year
- [ECCV24] MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization☆14Updated last year
- Official implementation of the paper: "A deeper look at depth pruning of LLMs"☆15Updated last year
- [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
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆67Updated 8 months ago