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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. 93991
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    INDEX
    Explanations

    repeated mentions of "wet" in various contexts

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

    wet conditions and substances

    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
    bootstrapcdn
    -0.68
    richTextPanel
    -0.65
     препратки
    -0.61
     poichè
    -0.60
     AssemblyCompany
    -0.60
    kusen
    -0.59
    awtextra
    -0.57
     Persona
    -0.57
     moeite
    -0.57
    melidir
    -0.57
    POSITIVE LOGITS
     wet
    2.13
    Wet
    2.08
     Wet
    2.06
    wet
    1.99
     WET
    1.66
    WET
    1.63
     wetter
    1.27
     wetting
    1.18
    湿
    1.03
     basah
    0.98
    Activations Density 0.005%

    No Known Activations