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    3. 10-GEMMASCOPE-RES-131K
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    words related to technical contexts

    np_acts-logits-general · gemini-2.5-flash-lite

    The neuron fires on content‐bearing tokens such as Chinese characters in key terms (e.g. 成, 本, 圣) and multi‐part identifiers or proper names in code and text (e.g. DateOfBirth, ErrorMsg, cheng, seong), so it’s detecting named entities and technical identifiers.

    oai_token-act-pair · o4-miniTriggered by @jyhe0408
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    google/gemma-scope-27b-pt-res/layer_10/width_131k
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    No Configuration Found
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    IFrame
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    Negative Logits
    栳
    -2.92
    ⩴
    -2.64
    佧
    -2.58
    of
    -2.52
    to
    -2.50
    quirer
    -2.42
    鶿
    -2.36
     cial
    -2.20
     revolves
    -2.19
    洒落
    -2.16
    POSITIVE LOGITS
    ization
    3.03
    ’
    2.77
    ०
    2.36
    瑆
    2.31
    …”
    2.28
     tidak
    2.27
    糴
    2.22
    actéristi
    2.19
    شاركة
    2.16
     defend
    2.11
    Activations Density 0.001%

    No Known Activations