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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 16k
    9. 9-GEMMASCOPE-RES-16K
    11. 9433
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    Explanations

    references to medical terminology and pharmaceutical products or concepts

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

    containing "ara" or "ran"

    np_acts-logits-general · gemini-2.0-flash

    names ending in ar or an

    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-16k
    Configuration
    google/gemma-scope-9b-it-res/layer_9/width_16k/average_l0_88
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    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
    Not in Any Lists

    No Comments

    Negative Logits
     vectorielle
    -0.62
     giapp
    -0.54
     Ấ
    -0.52
     zví
    -0.50
     zís
    -0.50
     adquis
    -0.47
     aggiunto
    -0.44
     fós
    -0.44
     acrylique
    -0.43
     teplo
    -0.43
    POSITIVE LOGITS
    ane
    0.72
    ani
    0.71
    ale
    0.70
    ari
    0.69
    ata
    0.68
     Moran
    0.68
     Scherer
    0.67
    ana
    0.67
    aran
    0.67
    ara
    0.66
    Activations Density 2.469%

    No Known Activations