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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 37-GEMMASCOPE-RES-16K
    11. 5762
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    Explanations

    specific types of seafood and their preparation methods

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 37-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_37/width_16k/average_l0_124
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.37.hook_resid_post
    Hook Layer
    37
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     []:
    -0.43
    fazione
    -0.43
    pecabezas
    -0.42
    FromNib
    -0.41
    PushMatrix
    -0.41
    колад
    -0.40
     ades
    -0.39
     apple
    -0.38
     recovery
    -0.38
    SqlClient
    -0.38
    POSITIVE LOGITS
     seafood
    0.74
     lobster
    0.69
     Lobster
    0.67
     shellfish
    0.66
     Seafood
    0.64
    Seafood
    0.61
     crab
    0.60
    Lobster
    0.58
     Alaskan
    0.57
     lobsters
    0.57
    Activations Density 0.180%

    No Known Activations