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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 35-GEMMASCOPE-RES-16K
    11. 6328
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    Explanations

    references to airports and air travel

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 35-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_35/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.35.hook_resid_post
    Hook Layer
    35
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     kasarigan
    -0.88
    出版年
    -0.85
    SharedDtor
    -0.82
     estekak
    -0.82
    parsedMessage
    -0.75
     ModelExpression
    -0.73
     Chwiliwch
    -0.70
    脚注の使い方
    -0.69
    ьаж
    -0.69
    Personensuche
    -0.67
    POSITIVE LOGITS
     airport
    1.10
     airports
    0.95
     Airport
    0.86
    airport
    0.81
     aeropuerto
    0.79
     aeroporto
    0.73
     Aeropuerto
    0.71
    机场
    0.69
     Flughafen
    0.69
    Airport
    0.68
    Activations Density 0.230%

    No Known Activations