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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 30-GEMMASCOPE-RES-16K
    11. 9609
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    INDEX
    Explanations

    mentions of "wood" or related terms in various contexts

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

    "Wood" or its variants

    np_acts-logits-general · gemini-2.0-flash

    wood prefixes and names

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 30-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_30/width_16k/average_l0_120
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.30.hook_resid_post
    Hook Layer
    30
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     giornal
    -0.42
     disambiguazione
    -0.42
    cepan
    -0.40
    //!
    -0.39
    tabak
    -0.38
    icano
    -0.38
    ithub
    -0.37
     сро
    -0.36
    intu
    -0.36
    dafx
    -0.36
    POSITIVE LOGITS
     Wood
    0.83
    Wood
    0.80
     wood
    0.71
     WOOD
    0.70
     Holz
    0.64
    wood
    0.58
     woo
    0.57
     ウッド
    0.56
    WOOD
    0.56
     Woo
    0.54
    Activations Density 0.124%

    No Known Activations