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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 39-GEMMASCOPE-RES-16K
    11. 1857
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    Explanations

    mentions of hotel names and their features

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 39-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_39/width_16k/average_l0_131
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.39.hook_resid_post
    Hook Layer
    39
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    帖最后由
    -0.45
     שוליים
    -0.42
    IInterface
    -0.39
    unicaciones
    -0.38
    PreInfinity
    -0.37
     <>",
    -0.36
     kasarigan
    -0.36
    richTextPanel
    -0.36
    reordered
    -0.36
     maleta
    -0.35
    POSITIVE LOGITS
     JW
    0.69
     Sheraton
    0.68
     Hyatt
    0.65
    JW
    0.64
     Hilton
    0.64
     Crow
    0.63
     Fairmont
    0.63
     Radisson
    0.63
    Hy
    0.59
    Hilton
    0.59
    Activations Density 0.274%

    No Known Activations