Nvidia发布小型语言模型Nemotron-Nano-9B-v2，拥有9亿参数，较原版12亿大幅缩减，旨在单台A10GPU高效运行。该模型采用混合架构，适应实际部署需求，推动小型模型发展。
英伟达发布小型语言模型Nemotron-Nano-9B-V2，参数量90亿，专为高效推理设计。该模型在多项基准测试中表现优异，部分测试达到同类产品最高水平，旨在与麻省理工和谷歌的小型AI模型竞争，适用于智能手表和手机等设备。
Nvidia发布小型语言模型Nemotron-Nano-9B-v2，参数量90亿，较前代减少30亿，专为单个A10GPU优化。该模型在基准测试中表现优异，支持灵活控制推理功能，处理速度提升高达6倍，适用于多种应用场景。
bartowski
这是NVIDIA Nemotron-Nano-9B-v2模型的量化版本，使用llama.cpp b6317版本进行量化处理。该模型提供了多种量化选项，包括bf16、Q8_0、Q6_K_L等，适用于不同的硬件和使用场景，方便用户部署和使用。
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