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首个针对Mamba系列模型的综合性PTQ设计，实验表明，MambaQuant能够将权重和激活值量化为8位，且基于Mamba的视觉和语言任务的准确率损失均小于1%。 >>加入极市CV技术交流群，走在计算机视觉的最前沿 宣传一下我们被人工智能顶会ICLR-2025录用的文章，MambaQuant：
2025 Chevrolet Malibu Instrument Cluster User Guide Auto User Guide While many large-scale Mamba-based models have been proposed, efficiently adapting pre-trained Mamba-based models to downstream tasks remains unexplored.In this paper, we conduct an. 26 Sept 2024 (modified: 05 Feb 2025) Submitted to ICLR 2025 Everyone Revisions BibTeX CC BY 4.0 Keywords : Pathological image classification, Mamba model, Self-supervised learning Abstract : Extracting visual representations is a crucial challenge in the domain of computational histopathology. Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient
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Iclr 2025 Accepted Papers For Publication Yvonne W. Lauderdale . 首个针对Mamba系列模型的综合性PTQ设计，实验表明，MambaQuant能够将权重和激活值量化为8位，且基于Mamba的视觉和语言任务的准确率损失均小于1%。 >>加入极市CV技术交流群，走在计算机视觉的最前沿 Recently, Mamba, a State Space Model (SSM)-based model, has attracted attention as a potential alternative to Transformers
Mamba Iclr 2024 Ford Loni Clarisse . MambaQuant achieves less than 1% accuracy loss in quantizing weights and activations to 8-bit for various Mamba-based tasks, marking the first comprehensive PTQ design for this family Abstract: Mamba is an efficient sequence model that rivals Transformers and demonstrates significant potential as a foundational architecture for various tasks