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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 14-GEMMASCOPE-RES-16K
    11. 5703
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    Explanations

    references to wearing clothing or accessories

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 14-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_14/width_16k/average_l0_67
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.14.hook_resid_post
    Hook Layer
    14
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    HandlerContext
    -0.54
    tisgarh
    -0.54
    PyExc
    -0.52
     Keyes
    -0.51
    BindingResult
    -0.50
    WebElementEntity
    -0.49
     fist
    -0.49
    INSEE
    -0.48
     endblock
    -0.48
    Grüsse
    -0.48
    POSITIVE LOGITS
     Wear
    1.14
    Wear
    1.11
     wear
    1.05
     WEAR
    1.02
    wearing
    0.98
    wear
    0.97
    Wearing
    0.94
     wearing
    0.93
     Wearing
    0.93
     worn
    0.90
    Activations Density 0.039%

    No Known Activations