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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 34-GEMMASCOPE-RES-16K
    11. 7468
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    Explanations

    references to quarterbacks in the context of football performance

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 34-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_34/width_16k/average_l0_114
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.34.hook_resid_post
    Hook Layer
    34
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     utafitiHapana
    -0.43
    gridy
    -0.39
     prakti
    -0.39
    corbic
    -0.37
    corpions
    -0.37
    fsen
    -0.36
    visualization
    -0.35
    춤
    -0.35
     piacere
    -0.35
     infinity
    -0.35
    POSITIVE LOGITS
     throwing
    0.80
     quarterback
    0.79
     quarterbacks
    0.77
     Throwing
    0.77
     throw
    0.77
     throws
    0.75
     threw
    0.75
     QB
    0.74
    throwing
    0.73
     passer
    0.72
    Activations Density 0.141%

    No Known Activations