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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 16k
    9. 9-GEMMASCOPE-RES-16K
    11. 9368
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    Explanations

    references to mountains or mountainous landscapes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    Texts about mountain locations

    np_acts-logits-general · gemini-2.0-flash

    mountainous areas and terrain

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B-IT @ 9-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-it-res/layer_9/width_16k/average_l0_88
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.9.hook_resid_post
    Hook Layer
    9
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Jeffries
    -0.44
     CFA
    -0.44
     brief
    -0.40
    ifred
    -0.40
     Modi
    -0.39
    CFA
    -0.38
     Leclerc
    -0.38
    brief
    -0.38
    rxjs
    -0.38
     промо
    -0.38
    POSITIVE LOGITS
    Mountain
    1.88
     Mountain
    1.88
     mountain
    1.84
     MOUNTAIN
    1.73
    mountain
    1.70
     mountains
    1.57
     Mountains
    1.52
     hill
    1.48
    Mountains
    1.45
    mountains
    1.36
    Activations Density 0.179%

    No Known Activations