ChangyuanWang17 / APQ-DMLinks
This is the official pytorch implementation for the paper: Towards Accurate Post-training Quantization for Diffusion Models.(CVPR24 Poster Highlight)
☆38Updated last year
Alternatives and similar repositories for APQ-DM
Users that are interested in APQ-DM are comparing it to the libraries listed below
Sorting:
- [NeurIPS'24]Efficient and accurate memory saving method towards W4A4 large multi-modal models.☆93Updated last year
- [ICCV2025]Generate one 2K image on single 24GB 3090 GPU!☆81Updated 4 months ago
- [CVPR 2024 Highlight & TPAMI 2025] This is the official PyTorch implementation of "TFMQ-DM: Temporal Feature Maintenance Quantization for…☆108Updated 3 months ago
- (ICLR 2025) BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models☆26Updated last year
- Implementation of Post-training Quantization on Diffusion Models (CVPR 2023)☆140Updated 2 years ago
- ☆15Updated 9 months ago
- [CVPR 2025] Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers☆73Updated last year
- [ICCV 2025] QuEST: Efficient Finetuning for Low-bit Diffusion Models☆55Updated 6 months ago
- [CVPR'23] SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer☆78Updated last year
- [ICLR 2024 Spotlight] This is the official PyTorch implementation of "EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Di…☆66Updated last year
- Denoising Diffusion Step-aware Models (ICLR2024)☆62Updated last year
- [ICLR'25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation☆145Updated 9 months ago
- [NeurIPS 2024] Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching☆116Updated last year
- [CVPR 2025] CoDe: Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient☆108Updated 3 months ago
- [ICML 2025] This is the official PyTorch implementation of "ZipAR: Accelerating Auto-regressive Image Generation through Spatial Locality…☆53Updated 9 months ago
- [ICCV 23]An approach to enhance the efficiency of Vision Transformer (ViT) by concurrently employing token pruning and token merging tech…☆104Updated 2 years ago
- [NeurIPS 2023] Structural Pruning for Diffusion Models☆213Updated last year
- The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"☆73Updated 9 months ago
- FORA introduces simple yet effective caching mechanism in Diffusion Transformer Architecture for faster inference sampling.☆52Updated last year
- [ICCV 2025] QuantCache:Adaptive Importance-Guided Quantization with Hierarchical Latent and Layer Caching for Video Generation☆15Updated 3 months ago
- [CVPR 2025] DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention☆176Updated 10 months ago
- torch_quantizer is a out-of-box quantization tool for PyTorch models on CUDA backend, specially optimized for Diffusion Models.☆22Updated last year
- [CVPR 2025] The official implementation of "CacheQuant: Comprehensively Accelerated Diffusion Models"☆41Updated 2 months ago
- ☆92Updated 9 months ago
- [ICCV2025 highlight]Rectifying Magnitude Neglect in Linear Attention☆56Updated 5 months ago
- ☆189Updated 11 months ago
- [ICLR 2025] Mixture Compressor for Mixture-of-Experts LLMs Gains More☆65Updated 11 months ago
- Curated list of methods that focuses on improving the efficiency of diffusion models☆44Updated last year
- Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation☆80Updated 5 months ago
- [CVPR 2025 Highlight] TinyFusion: Diffusion Transformers Learned Shallow☆153Updated last month