6 papers
DreamLite: A Lightweight On-Device Unified Model for Image Generation and Editing
Kailai Feng, Yuxiang Wei, Bo Chen +5
Diffusion models have made significant progress in both text-to-image (T2I) generation and text-guided image editing. However, these models are typically built with billions of par…
AngelSlim: A more accessible, comprehensive, and efficient toolkit for large model compression
Rui Cen, QiangQiang Hu, Hong Huang +10
This technical report introduces AngelSlim, a comprehensive and versatile toolkit for large model compression developed by the Tencent Hunyuan team. By consolidating cutting-edge a…
S2O: Early Stopping for Sparse Attention via Online Permutation
Yu Zhang, Songwei Liu, Chenqian Yan +4
Attention scales quadratically with sequence length, fundamentally limiting long-context inference. Existing block-granularity sparsification can reduce latency, but coarse blocks…
ERTACache: Error Rectification and Timesteps Adjustment for Efficient Diffusion
Xurui Peng, Chenqian Yan, Hong Liu +6
Diffusion models suffer from substantial computational overhead due to their inherently iterative inference process. While feature caching offers a promising acceleration strategy…
Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion
Songwei Liu, Chao Zeng, Chenqian Yan +4
Diffusion models have transformed image synthesis by establishing unprecedented quality and creativity benchmarks. Nevertheless, their large-scale deployment faces challenges due t…
GQSA: Group Quantization and Sparsity for Accelerating Large Language Model Inference
Chao Zeng, Songwei Liu, Shu Yang +3
Model compression has emerged as a mainstream solution to reduce memory usage and computational overhead. This paper presents Group Quantization and Sparse Acceleration (GQSA), a n…