NNsight和NDIF：使得访问基础模型内部更加民主化

NNsight and NDIF: Democratizing Access to Foundation Model Internals

July 18, 2024

作者: Jaden Fiotto-Kaufman, Alexander R Loftus, Eric Todd, Jannik Brinkmann, Caden Juang, Koyena Pal, Can Rager, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Michael Ripa, Adam Belfki, Nikhil Prakash, Sumeet Multani, Carla Brodley, Arjun Guha, Jonathan Bell, Byron Wallace, David Bau

cs.AI

摘要

目前最先进的基础模型规模巨大，这限制了科学家们的接触，因为在大型模型上进行定制实验需要昂贵的硬件和复杂的工程，这对大多数研究人员来说是不切实际的。为了缓解这些问题，我们引入了NNsight，这是一个开源的Python软件包，具有简单灵活的API，可以通过构建计算图在任何PyTorch模型上表达干预。我们还推出了NDIF，这是一个协作研究平台，通过NNsight API为研究人员提供访问基础规模LLMs的途径。代码、文档和教程可在https://www.nnsight.net 上找到。

English

The enormous scale of state-of-the-art foundation models has limited their accessibility to scientists, because customized experiments at large model sizes require costly hardware and complex engineering that is impractical for most researchers. To alleviate these problems, we introduce NNsight, an open-source Python package with a simple, flexible API that can express interventions on any PyTorch model by building computation graphs. We also introduce NDIF, a collaborative research platform providing researchers access to foundation-scale LLMs via the NNsight API. Code, documentation, and tutorials are available at https://www.nnsight.net.