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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 31-GEMMASCOPE-RES-16K
    11. 8096
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    Explanations

    references to road conditions and the potential impact on vehicles

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

    descriptions of physical infrastructure and structural features like roads, paths, barriers, and medians.

    oai_token-act-pair · claude-4-5-haikuTriggered by @emiglarou
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 31-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_31/width_16k/average_l0_114
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.31.hook_resid_post
    Hook Layer
    31
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Numerade
    -0.60
    Personendaten
    -0.44
     demografica
    -0.43
    ViewImports
    -0.42
    RoutingModule
    -0.42
     circ
    -0.42
     StringVar
    -0.41
    AddTagHelper
    -0.40
    bronn
    -0.39
    {(-
    -0.39
    POSITIVE LOGITS
     roadside
    0.86
     sidewalk
    0.75
     side
    0.73
     shoulder
    0.67
     median
    0.65
     lane
    0.64
    side
    0.64
     shoulders
    0.63
     lanes
    0.61
     curb
    0.60
    Activations Density 0.168%

    No Known Activations