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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 131k
    9. 9-GEMMASCOPE-RES-131K
    11. 23704
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    Explanations

    references to different types of cheese and their preparation

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

    cheese and cheese types

    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-131k
    Configuration
    google/gemma-scope-9b-it-res/layer_9/width_131k/average_l0_121
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    131,072
    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
    AsUp
    -0.52
     desierto
    -0.51
    équences
    -0.50
     jäl
    -0.47
     bambú
    -0.47
     sonriente
    -0.46
     belangrij
    -0.45
     braccia
    -0.45
     anzi
    -0.45
     orgánico
    -0.45
    POSITIVE LOGITS
     Cheese
    1.00
     cheese
    1.00
     cheeses
    0.90
    cheese
    0.87
    Cheese
    0.84
    migiano
    0.77
     cheddar
    0.76
    🧀
    0.73
     mozzarella
    0.71
     fromage
    0.67
    Activations Density 0.069%

    No Known Activations