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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 16k
    9. 9-GEMMASCOPE-RES-16K
    11. 337
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    INDEX
    Explanations

    brand names and model identifiers associated with vehicles

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot

    Car brands

    np_acts-logits-general · gemini-2.0-flash

    car makes

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B-IT @ 9-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-it-res/layer_9/width_16k/average_l0_88
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.9.hook_resid_post
    Hook Layer
    9
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
     Unterscheidung
    -0.34
     añad
    -0.31
     ochron
    -0.28
     macetas
    -0.28
     Kräfte
    -0.27
     Reised
    -0.27
     angeb
    -0.27
     Decke
    -0.26
     mogelijkheden
    -0.26
     Anleitung
    -0.26
    POSITIVE LOGITS
     Chevrolet
    0.92
     Audi
    0.91
     Nissan
    0.90
    Chevrolet
    0.88
    Audi
    0.88
    Volvo
    0.88
     Volvo
    0.88
     Volkswagen
    0.88
     Ford
    0.88
     Mercedes
    0.86
    Activations Density 0.493%

    No Known Activations