Massive SAEs: other objectives

SAEs from Massive Activations Confound Sparse Autoencoders. Main SAEs: nathandelisle/massive-saes.

The paper's comparison of SAE training objectives (TopK, BatchTopK, ReLU + L1), repeated over five seeds for eight models at the same layers as the main SAEs. Each objective has standard and bypass versions.

Files: <model>/<objective>/block<L>/<standard|bypass>/seed<k>/{sae.pt, config.json}. The mean and PC1 for each model are in the main repo under <model>/preprocessing/.

Load a checkpoint with torch.load(path, map_location="cpu", weights_only=True).

License: CC BY 4.0. The base models' own licenses also apply.

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