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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 10-GEMMASCOPE-RES-16K
    11. 15573
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    Explanations

    references to hunting and food preparation practices

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 10-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_10/width_16k/average_l0_113
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.10.hook_resid_post
    Hook Layer
    10
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Personendaten
    -0.56
    ArrowToggle
    -0.51
    出版年
    -0.47
     שוליים
    -0.44
    Rhestr
    -0.44
    sidemargin
    -0.42
    Linki
    -0.41
     FetchType
    -0.40
    kinci
    -0.40
     disambiguazione
    -0.40
    POSITIVE LOGITS
     meat
    0.58
     hunts
    0.56
     hunting
    0.54
     hunted
    0.54
    hunting
    0.53
    Meat
    0.51
    Hunting
    0.50
     butcher
    0.49
     MEAT
    0.49
     Hunting
    0.49
    Activations Density 0.309%

    No Known Activations