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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. 8486
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    INDEX
    Explanations

    descriptions of clothing and their condition

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

    Worn or damaged clothing

    np_acts-logits-general · gemini-2.0-flash

    clothing condition and maintenance

    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
     desvi
    -0.40
    Sco
    -0.40
     suor
    -0.39
     aikaa
    -0.39
     magasiner
    -0.39
     suces
    -0.37
     comprim
    -0.37
     confusión
    -0.36
     COMPAR
    -0.36
    empor
    -0.36
    POSITIVE LOGITS
     worn
    0.63
     ब्रेकडाउन
    0.62
     nahilalakip
    0.56
    ftagPool
    0.54
    ulemon
    0.53
     متحده
    0.52
     Worn
    0.52
     clothes
    0.47
     washable
    0.46
     washes
    0.44
    Activations Density 0.259%

    No Known Activations