Instructions to use chanind/sae-gemma-2-2b-standard-high-l0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SAELens
How to use chanind/sae-gemma-2-2b-standard-high-l0 with SAELens:
# pip install sae-lens from sae_lens import SAE sae, cfg_dict, sparsity = SAE.from_pretrained( release = "RELEASE_ID", # e.g., "gpt2-small-res-jb". See other options in https://github.com/jbloomAus/SAELens/blob/main/sae_lens/pretrained_saes.yaml sae_id = "SAE_ID", # e.g., "blocks.8.hook_resid_pre". Won't always be a hook point ) - Notebooks
- Google Colab
- Kaggle
SAEs for use with the SAELens library
This repository contains the following SAEs:
- 166670336
- 500002816
- 666669056
- 833335296
- 333336576
- 1000001536
Load these SAEs using SAELens as below:
from sae_lens import SAE
sae, cfg_dict, sparsity = SAE.from_pretrained("chanind/sae-gemma-2-2b-standard-high-l0", "<sae_id>")
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