In our recent interpretability research, we introduced a new method to trace the thoughts of a large language model. Today, we’re open-sourcing the method so that anyone can build on our research.Our approach is to generate attribution graphs, which (partially) reveal the steps a model took internally to decide on a particular output. The open-source library we’re releasing supports the generation of attribution graphs on popular open-weights models—and a frontend hosted by Neuronpedia lets you ...