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- license: apache-2.0
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- # 1. GemmaScope
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- Gemmascope is TODO
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- # 2. What Is `gemmascope-9b-pt-att`?
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- - `gemmascope-`: See 1.
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- - `9b-pt-`: These SAEs were trained on the Gemma v2 9B base model (TODO link).
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- - `att`: These SAEs were trained on the attention layer outputs, before the final linear projection (TODO link ckkissane post).
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- ## 3. GTM FAQ (TODO(conmy): delete for main rollout)
 
 
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- Q1: Why does this model exist in `gg-hf`?
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- A1: See https://docs.google.com/document/d/1bKaOw2mJPJDYhgFQGGVOyBB3M4Bm_Q3PMrfQeqeYi0M (Google internal only).
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- Q2: What does "SAE" mean?
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- A2: Sparse Autoencoder. See https://docs.google.com/document/d/1roMgCPMPEQgaNbCu15CGo966xRLToulCBQUVKVGvcfM (should be available to trusted HuggingFace collaborators, and Google too).
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- TODO(conmy): remove this when making the main repo.
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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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+ license: cc-by-4.0
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+ # 1. Gemma Scope
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+ Gemma Scope is a comprehensive, open suite of sparse autoencoders for Gemma 2 9B and 2B. Sparse Autoencoders are a "microscope" of sorts that can help us break down a model’s internal activations into the underlying concepts, just as biologists use microscopes to study the individual cells of plants and animals.
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+ See our [landing page](https://huggingface.co/google/gemma-scope) for details on the whole suite. This is a specific set of SAEs:
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+ # 2. What Is `gemma-scope-9b-pt-att`?
 
 
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+ - `gemma-scope-`: See 1.
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+ - `9b-pt-`: These SAEs were trained on Gemma v2 27B base model.
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+ - `att`: These SAEs were trained on the model's attention layer output before the linear projection.
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+ ## 3. Point of Contact
 
 
 
 
 
 
 
 
 
 
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  Point of contact: Arthur Conmy
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