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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. 107185
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    INDEX
    Explanations

    references to cheese and cheese-related dishes

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

    cheese, cheesy, queso

    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
     congi
    -0.42
    Annexes
    -0.39
     Kuli
    -0.36
    vânt
    -0.36
     poč
    -0.36
    рет
    -0.36
    wirkung
    -0.35
    Biographie
    -0.35
     Longitudinal
    -0.35
     vogli
    -0.35
    POSITIVE LOGITS
     cheese
    1.26
     Cheese
    1.23
    Cheese
    1.20
    cheese
    1.12
     chees
    1.09
     cheesy
    1.07
     cheeses
    1.05
     Chees
    0.97
    🧀
    0.90
     queso
    0.88
    Activations Density 0.013%

    No Known Activations