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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-2B
    7. Residual Stream - 16k
    9. 16-GEMMASCOPE-RES-16K
    11. 7033
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    INDEX
    Explanations

    terms related to financial crime, particularly money laundering

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

    crime and law enforcement

    np_acts-logits-general · gemini-2.0-flash

    crime, fraud, laundering, indictment

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-2B @ 16-gemmascope-res-16k
    Configuration
    google/gemma-scope-2b-pt-res/layer_16/width_16k/average_l0_78
    Prompts (Dashboard)
    36,864 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.16.hook_resid_post
    Hook Layer
    16
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    RegressionTest
    -0.81
     <<<<<<<<<<<<<<
    -0.63
    Tembelea
    -0.61
    Vidite
    -0.55
    featureID
    -0.55
    UnitTesting
    -0.54
    WithIOException
    -0.54
    <?
    -0.53
     ModelExpression
    -0.52
    Gön
    -0.52
    POSITIVE LOGITS
     fenomeno
    0.80
     criminal
    0.79
     rampant
    0.78
     illegal
    0.78
     illicit
    0.77
     enforcement
    0.76
     crimes
    0.76
     prevention
    0.74
     crackdown
    0.74
     crime
    0.72
    Activations Density 0.225%

    No Known Activations