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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. 601
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    INDEX
    Explanations

    references to various types of goods and their usage in different contexts

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

    "goods" (often capitalized)

    np_acts-logits-general · gemini-2.0-flash

    commercial goods and items

    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
     Meksiko
    -0.46
     aparcamiento
    -0.41
     Moskau
    -0.41
     Jurí
    -0.40
     Schles
    -0.40
     publicidad
    -0.40
     autobuses
    -0.39
     vocación
    -0.39
     opération
    -0.39
     conciertos
    -0.38
    POSITIVE LOGITS
     goods
    1.52
     Goods
    1.30
    goods
    1.20
    Goods
    1.15
     goederen
    1.10
     GOODS
    1.08
     items
    1.03
     Items
    0.91
    物品
    0.90
     products
    0.90
    Activations Density 0.534%

    No Known Activations