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 / organization | Transluce |
|---|---|
| License (as declared) | mit |
| Downloads | 155 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 17 December 2025 |
| Last updated at source | 3 January 2026 |
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