imagination-research / LCSC
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
☆14Updated 8 months ago
Alternatives and similar repositories for LCSC:
Users that are interested in LCSC are comparing it to the libraries listed below
- [Preprint] Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Prunin…☆40Updated last year
- BESA is a differentiable weight pruning technique for large language models.☆14Updated 9 months ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆36Updated 9 months ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆20Updated 9 months ago
- PyTorch code for Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers☆36Updated 3 months ago
- ☆21Updated last month
- [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models☆27Updated 6 months ago
- [NeurIPS 2024] Search for Efficient LLMs☆9Updated last month
- ☆8Updated 2 months ago
- [ECCV24] MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization☆10Updated 3 weeks ago
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆24Updated 3 years ago
- [ICML 2024] Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity; Lu Yin*, Ajay Jaiswal*, Shiwei Liu, So…☆15Updated 6 months ago
- Official Code For Dual Grained Quantization: Efficient Fine-Grained Quantization for LLM☆13Updated 11 months ago
- torch_quantizer is a out-of-box quantization tool for PyTorch models on CUDA backend, specially optimized for Diffusion Models.☆21Updated 8 months ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 2 years ago
- This is a PyTorch implementation of the paperViP A Differentially Private Foundation Model for Computer Vision☆37Updated last year
- [TMLR] Official PyTorch implementation of paper "Efficient Quantization-aware Training with Adaptive Coreset Selection"☆30Updated 3 months ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆31Updated last year
- Benchmarking Attention Mechanism in Vision Transformers.☆17Updated 2 years ago
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆25Updated 2 months ago
- [ECCV 2022] SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning☆19Updated 2 years ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆29Updated 5 months ago
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆37Updated 8 months ago
- [Neurips 2022] “ Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropogation”, Ziyu Jiang*, Xuxi Chen*, Xueqin Huan…☆19Updated last year
- LLM Inference with Microscaling Format☆11Updated last month
- ☆11Updated 6 months ago
- ACL 2023☆38Updated last year
- [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…☆23Updated 2 years ago
- [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models☆17Updated 6 months ago
- DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training (ICLR 2023)☆30Updated last year