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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 8-GEMMASCOPE-RES-16K
    11. 6760
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    Explanations

    mentions of various types of pants and trousers

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 8-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_8/width_16k/average_l0_99
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.8.hook_resid_post
    Hook Layer
    8
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     للاسماء
    -0.56
    AnchorStyles
    -0.56
    最快更新
    -0.48
     mauva
    -0.45
     plufieurs
    -0.44
     increí
    -0.44
    UnknownFields
    -0.43
    StoreMessageInfo
    -0.43
    CIUDAD
    -0.43
     Caspian
    -0.43
    POSITIVE LOGITS
     pants
    1.21
     Pants
    1.09
     jeans
    1.04
     trousers
    1.03
    pants
    0.98
    Pants
    0.92
     Jeans
    0.88
     trouser
    0.87
    Jeans
    0.80
     broek
    0.79
    Activations Density 0.162%

    No Known Activations