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decoderesearch/olmo-3-saes
olmo-3-saes is a machine learning model from decoderesearch. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for saelens.
This repository contains the following SAEs:
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Updated Aug 9, 2026
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From the Hugging Face model README
This repository contains the following SAEs:
Load these SAEs using SAELens as below:
from sae_lens import SAE
sae = SAE.from_pretrained("decoderesearch/olmo-3-saes", "<sae_id>")
These SAEs are all Matryoshka BatchTopK SAEs trained on 1B tokens of the Pile Uncopyrighted using SAELens. The SAEs each have width 65k latents, and 2 inner Matryoshka prefixes of 2k latents and 16k latents.
For complete details of how these SAEs were trained, refer to the runner_cfg.json in each SAE directory.
This config includes all hyperparameters passed to the SAELens trainer when training the SAEs.
@misc{decode2026olmo3saes,
author = {Chanin, David and Lin, Johnny},
title = {{Olmo-3} Sparse Autoencoders},
year = {2026},
organization = {Decode Research},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/decoderesearch/olmo-3-saes}}
}
These SAEs were trained thanks to compute provided by Modal.