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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 40-GEMMASCOPE-RES-16K
    11. 5820
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    Explanations

    references to transportation systems and urban transit options

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 40-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_40/width_16k/average_l0_125
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.40.hook_resid_post
    Hook Layer
    40
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    SequentialGroup
    -0.52
    олові
    -0.51
    FunctionFlags
    -0.49
    #+#
    -0.48
    WebElementEntity
    -0.40
    PyExc
    -0.39
     Meksiku
    -0.39
    ManagedBean
    -0.39
     IBOutlet
    -0.39
    windowFixed
    -0.39
    POSITIVE LOGITS
     Metro
    0.94
     subway
    0.94
     metro
    0.93
     métro
    0.85
     underground
    0.83
    Metro
    0.81
    metro
    0.78
     METRO
    0.77
     riders
    0.73
     метро
    0.72
    Activations Density 0.358%

    No Known Activations