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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-2B
    7. MLP Out - 16k
    9. 19-GEMMASCOPE-MLP-16K
    11. 10179
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    Explanations

    references to dietary fats and their classifications

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-2B @ 19-gemmascope-mlp-16k
    Configuration
    google/gemma-scope-2b-pt-mlp/layer_19/width_16k/average_l0_109
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.19.hook_mlp_out
    Hook Layer
    19
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    webElementXpaths
    -0.88
    AddTagHelper
    -0.81
    Personendaten
    -0.75
    Autoritní
    -0.73
    PerformLayout
    -0.71
    sizeCache
    -0.67
    Xna
    -0.61
    LookAnd
    -0.59
    styleType
    -0.57
     nonUne
    -0.57
    POSITIVE LOGITS
     fat
    0.79
    fat
    0.70
     fats
    0.64
     Fat
    0.64
     FAT
    0.61
    Fat
    0.60
     sour
    0.54
     fatty
    0.53
    amanca
    0.51
    achev
    0.50
    Activations Density 0.377%

    No Known Activations