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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 37-GEMMASCOPE-RES-16K
    11. 8115
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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 @ 37-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_37/width_16k/average_l0_124
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.37.hook_resid_post
    Hook Layer
    37
    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
    -0.70
    出版年
    -0.66
    SharedDtor
    -0.52
    脚注の使い方
    -0.51
     MainAxisSize
    -0.51
     GenerationType
    -0.49
    InitVars
    -0.49
    niająca
    -0.49
    parsedMessage
    -0.48
    󠁬
    -0.48
    POSITIVE LOGITS
     airport
    1.30
     airports
    1.09
     Airport
    1.05
    airport
    1.00
     aeropuerto
    0.99
    Airport
    0.90
    机场
    0.89
     aeroporto
    0.87
     Airports
    0.87
     Flughafen
    0.87
    Activations Density 0.284%

    No Known Activations