This is a simulator model used to score candidate natural-language explanations of internal features in Llama-3.1-8B. Given:

the simulator predicts where the described feature should activate in the sequence (token-level activation scores). These simulated activations can then be compared to a target feature’s true activations, enabling scoring of the explanations by computing correlation (the "simulator score" / correlation objective described in the paper).

Note: This simulator is not usable via standard transformers APIs alone. You must first clone and install our repository, which provides the custom simulator wrapper and scoring utilities.