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    1. Home
    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 131k
    9. 9-GEMMASCOPE-RES-131K
    11. 4453
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    INDEX
    Explanations

    terms related to aging and cosmetic procedures, particularly focused on skin and wrinkles

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

    wrinkles and Botox

    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
    SequentialGroup
    -0.55
    samp
    -0.49
    andon
    -0.47
    ⓘ
    -0.46
    Sora
    -0.45
     Boba
    -0.45
     BIBSYS
    -0.44
    jago
    -0.44
     Samar
    -0.43
    Portail
    -0.43
    POSITIVE LOGITS
     wrinkles
    2.09
     wrinkle
    1.73
     wrink
    1.52
     wrinkled
    1.48
     Wr
    1.16
    皺
    0.98
    Wr
    0.94
    皱
    0.91
    wr
    0.77
    inkles
    0.75
    Activations Density 0.002%

    No Known Activations