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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 23-GEMMASCOPE-RES-16K
    11. 1781
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    Explanations

    references to different types of materials, particularly wood and metal

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 23-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_23/width_16k/average_l0_120
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.23.hook_resid_post
    Hook Layer
    23
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Bewußt
    -0.47
     împre
    -0.43
     følge
    -0.42
     ketat
    -0.42
     conoz
    -0.41
     quedado
    -0.41
     desay
    -0.41
     Beobach
    -0.41
     afec
    -0.40
     pulseras
    -0.40
    POSITIVE LOGITS
     leather
    0.68
    aarrggbb
    0.65
     rubber
    0.63
     BrowserModule
    0.62
     Plastic
    0.61
    phalt
    0.60
     Rubber
    0.60
    ########.
    0.59
    ButterKnife
    0.59
     wool
    0.57
    Activations Density 0.599%

    No Known Activations