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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 30-GEMMASCOPE-RES-16K
    11. 8684
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    Explanations

    references to airlines and related entities in the context of aviation operations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    Following "Bank" or "Banks"

    np_acts-logits-general · gemini-2.0-flash

    bank and airline names

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 30-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_30/width_16k/average_l0_120
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.30.hook_resid_post
    Hook Layer
    30
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    atoga
    -0.38
     Larsson
    -0.37
    Inline
    -0.35
    HasMaxLength
    -0.34
     Auft
    -0.33
     immersion
    -0.32
     ['./
    -0.32
     Deane
    -0.32
     Magdal
    -0.32
     eu
    -0.31
    POSITIVE LOGITS
     banks
    1.04
     bank
    0.93
    banks
    0.92
     banques
    0.89
     banking
    0.87
     Bank
    0.86
     carrier
    0.83
     carriers
    0.83
     airlines
    0.82
    abank
    0.82
    Activations Density 0.341%

    No Known Activations