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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-2B
    7. Residual Stream - 16k
    9. 22-GEMMASCOPE-RES-16K
    11. 122
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    INDEX
    Explanations

    phrases related to transportation and logistics

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot

    Transportation-related terms, especially buses and trains

    np_acts-logits-general · gemini-2.0-flash

    modes of transport

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-2B @ 22-gemmascope-res-16k
    Configuration
    google/gemma-scope-2b-pt-res/layer_22/width_16k/average_l0_72
    Prompts (Dashboard)
    36,864 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.22.hook_resid_post
    Hook Layer
    22
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    脚注の使い方
    -0.58
    Zunanje
    -0.57
    tagHelperRunner
    -0.56
     ujednoznacz
    -0.51
     vicenda
    -0.50
    marginHorizontal
    -0.50
     soste
    -0.50
     itinerary
    -0.49
    dega
    -0.47
    Trip
    -0.47
    POSITIVE LOGITS
     train
    1.25
     bus
    1.13
     trains
    1.06
    train
    1.01
     Train
    0.97
     buses
    0.91
     TRAIN
    0.90
    Train
    0.89
     Trains
    0.86
     rail
    0.85
    Activations Density 0.159%

    No Known Activations