Search results for computer+%3e+ai%2fml+%3e+language+processing

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Quamba2: a robust and scalable post-training quantization framework for selective state space models (SSMs)
Quamba2 highlights Supports W4A8 / W4A16 / W4AX / W8A8 for Mamba1 and Mamba2 Achieves 4x memory reduction and 3x generation speedup Enables 8B model inference on Orin Nano 8G at 13 tokens/sec Outperforms W4A8KV4 Llama3-8B in both speed and quality Background Deploying state space models (SSMs), which excel at processing long sequences but demand...
Quamba: Post-training quantization for selective state space models
Background State Space Models (SSMs) are integral to numerous advanced technologies, including natural language processing, robotics, autonomous vehicles, and edge computing systems. As these applications increasingly demand real-time processing and intelligent decision-making on devices with limited computa­tional resources, there is a pressing...