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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 16-GEMMASCOPE-RES-16K
    11. 12711
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    references to specific sneaker brands and models

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 16-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_16/width_16k/average_l0_75
    Prompts (Dashboard)
    24,576 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
    SourceChecksum
    -0.43
     invokingState
    -0.35
    )))),
    -0.33
     voud
    -0.31
     Económica
    -0.31
    Datuak
    -0.30
     grou
    -0.30
    _));
    -0.28
     ProtoMessage
    -0.28
     Bette
    -0.28
    POSITIVE LOGITS
     EconPapers
    0.82
     sneaker
    0.64
     streetwear
    0.61
     iconic
    0.58
    AutoModerator
    0.58
    Swatch
    0.57
    figer
    0.56
     Nike
    0.56
     brand
    0.56
    はじめに
    0.55
    Activations Density 0.052%

    No Known Activations