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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 131k
    9. 9-GEMMASCOPE-RES-131K
    11. 81155
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    INDEX
    Explanations

    references to a specific dish, particularly comfort foods like mac and cheese

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot

    food and pasta dishes

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B-IT @ 9-gemmascope-res-131k
    Configuration
    google/gemma-scope-9b-it-res/layer_9/width_131k/average_l0_121
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    131,072
    Data Type
    float32
    Hook Name
    blocks.9.hook_resid_post
    Hook Layer
    9
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
     Nucl
    -0.30
     Consulate
    -0.29
     aéreas
    -0.28
    ledem
    -0.28
     gift
    -0.28
    COHOL
    -0.28
     ffilmiau
    -0.28
    èdia
    -0.27
    codecs
    -0.26
    msgSender
    -0.26
    POSITIVE LOGITS
     macaroni
    0.87
     queſta
    0.67
     cheese
    0.67
    cheese
    0.66
    ChildScrollView
    0.65
     pasta
    0.64
     Cheese
    0.62
     spaghetti
    0.60
    spaghetti
    0.60
    pasta
    0.59
    Activations Density 0.001%

    No Known Activations