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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 23-GEMMASCOPE-RES-16K
    11. 3831
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    Explanations

    instances involving airports or travel-related events

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 23-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_23/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.23.hook_resid_post
    Hook Layer
    23
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     aprendizagem
    -0.52
     divulgação
    -0.45
     riego
    -0.45
     garagem
    -0.44
    deutig
    -0.43
     pareti
    -0.42
     instituição
    -0.42
     annual
    -0.40
    Personensuche
    -0.40
     conservación
    -0.40
    POSITIVE LOGITS
     airport
    0.95
    airport
    0.91
     airports
    0.85
     Airport
    0.84
     airline
    0.83
     airlines
    0.82
    Airport
    0.81
     passengers
    0.78
     baggage
    0.77
     luggage
    0.77
    Activations Density 0.149%

    No Known Activations