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Dataset · Hugging Face

Transluce/act_patch_llama_3.1_8b_counterfact

Training Language Models to Explain Their Own Computations Paper | Code This dataset contains activation patching results used for training explainer models to predict how internal interventions affect target model outputs. It was introduced in the paper "Training Language Models to Explain Their Own Computations". Dataset Summary The dataset covers the Activation Patching task for the Llama-3.1-8B target model, where explainer models learn to predict the effects… See the full description on the dataset page: https://huggingface.co/datasets/Transluce/act_patch_llama_3.1_8b_counterfact.

Author / organizationTransluce
License (as declared)mit
Downloads155 (as reported by Hugging Face)
Likes0
Created17 December 2025
Last updated at source3 January 2026
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