NNsight and NDIF: Democratizing Access to Foundation Model Internals
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.
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NNsight and NDIF: Democratizing Access to Foundation Model Internals
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.
neural graphs computation graphs PyTorch model open-source Python package foundation-scale LLMs collaborative research platform NNsight NDIF