SAELens
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@@ -16,7 +16,20 @@ See our [landing page](https://huggingface.co/google/gemma-scope) for details on
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  - `res`: These SAEs were trained on the model's residual stream.
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  - We include experimental SAEs trained on token embeddings in the ./embedding folder.
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- ## 3. Point of Contact
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Point of contact: Arthur Conmy
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@@ -28,3 +41,7 @@ Contact by email:
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  HuggingFace account:
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  https://huggingface.co/ArthurConmyGDM
 
 
 
 
 
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  - `res`: These SAEs were trained on the model's residual stream.
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  - We include experimental SAEs trained on token embeddings in the ./embedding folder.
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+ # 3. How can I use these SAEs straight away?
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+
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+ ```python
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+ from sae_lens import SAE # pip install sae-lens
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+
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+ sae, cfg_dict, sparsity = SAE.from_pretrained(
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+ release = "gemma-scope-9b-pt-res-canonical",
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+ sae_id = "layer_0/width_16k/canonical",
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+ )
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+ ```
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+
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+ See https://github.com/jbloomAus/SAELens for details on this library.
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+
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+ # 4. Point of Contact
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  Point of contact: Arthur Conmy
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  HuggingFace account:
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  https://huggingface.co/ArthurConmyGDM
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+ # 5. Citation
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+
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+ Paper: https://arxiv.org/abs/2408.05147