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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 34-GEMMASCOPE-RES-16K
    11. 2009
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    Explanations

    various aspects related to cheese and cheeseburgers

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 34-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_34/width_16k/average_l0_114
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.34.hook_resid_post
    Hook Layer
    34
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Beagle
    -0.51
     Khartoum
    -0.48
     propOrder
    -0.46
    WebMethod
    -0.45
    tanleria
    -0.45
    irut
    -0.45
     Vigo
    -0.44
     henna
    -0.44
    priority
    -0.43
     binh
    -0.43
    POSITIVE LOGITS
     cheese
    1.77
     Cheese
    1.48
    cheese
    1.40
     cheeses
    1.38
    Cheese
    1.38
    🧀
    1.20
     Käse
    1.20
    チーズ
    1.12
     cheddar
    1.12
     Cheddar
    0.98
    Activations Density 0.184%

    No Known Activations