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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. 6162
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    Explanations

    references to various types of clothing, particularly pants and jeans

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

    Clothing items: pants, jeans, trousers

    np_acts-logits-general · gemini-2.0-flash

    pants, trousers, jeans

    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
    UnknownFields
    -0.49
    CIUDAD
    -0.41
    StoreMessageInfo
    -0.39
    xima
    -0.36
     Micho
    -0.35
    RefNanny
    -0.34
    最快更新
    -0.33
    PERATURE
    -0.33
     Obrador
    -0.33
    核
    -0.32
    POSITIVE LOGITS
     pants
    1.29
     Pants
    1.16
     trousers
    1.14
     jeans
    1.03
    pants
    1.02
    Pants
    0.98
     trouser
    0.91
     broek
    0.87
     Jeans
    0.85
     pantaloni
    0.85
    Activations Density 0.107%

    No Known Activations