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    1. Home
    2. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    3. Gemma-2-9B-IT
    4. Residual Stream - 131k
    5. 9-GEMMASCOPE-RES-131K
    6. 28003
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    Explanations

    entries related to meals, specifically lunch and dining experiences

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

    lunch and breakfast times

    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
    Not in Any Lists

    No Comments

    Negative Logits
    izare
    -0.48
    FunctionFlags
    -0.46
     Atlántico
    -0.46
     interdit
    -0.45
    requireNonNull
    -0.44
    
    -0.44
    BlockingQueue
    -0.44
    HandlerContext
    -0.44
    ————————————————
    -0.43
     चीज़ों
    -0.43
    POSITIVE LOGITS
     lunch
    0.69
    lunch
    0.58
     Lunch
    0.56
     brunch
    0.53
    Lunch
    0.52
     dinner
    0.51
     lunches
    0.50
     pranzo
    0.50
     breakfast
    0.49
    RTLI
    0.47
    Activations Density 0.009%

    No Known Activations