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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-2B
    7. Residual Stream - 16k
    9. 22-GEMMASCOPE-RES-16K
    11. 2458
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    Explanations

    topics related to dietary patterns and health associations

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

    Unhealthy foods (high sugar, fast food)

    np_acts-logits-general · gemini-2.0-flash

    high sugar, fat, fast food

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-2B @ 22-gemmascope-res-16k
    Configuration
    google/gemma-scope-2b-pt-res/layer_22/width_16k/average_l0_72
    Prompts (Dashboard)
    36,864 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.22.hook_resid_post
    Hook Layer
    22
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    +:+
    -1.03
    queryInterface
    -0.93
     OFDb
    -0.91
     nahilalakip
    -0.83
    LookAnd
    -0.83
    WithIOException
    -0.73
    ьаж
    -0.73
     EconPapers
    -0.72
    MigrationBuilder
    -0.72
     CreateTagHelper
    -0.71
    POSITIVE LOGITS
     junk
    0.91
     unhealthy
    0.83
     sugary
    0.81
     processed
    0.80
     sugar
    0.78
     fast
    0.77
     harmful
    0.72
    junk
    0.66
     preservatives
    0.66
     excessive
    0.65
    Activations Density 0.319%

    No Known Activations