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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B-IT
    7. Residual Stream - 131k
    9. 31-GEMMASCOPE-RES-131K
    11. 61882
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    Explanations

    terms related to pulp and slurry processing in industrial contexts

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

    wood and paper production

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B-IT @ 31-gemmascope-res-131k
    Configuration
    google/gemma-scope-9b-it-res/layer_31/width_131k/average_l0_109
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    131,072
    Data Type
    float32
    Hook Name
    blocks.31.hook_resid_post
    Hook Layer
    31
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    findpost
    -0.48
    ModelSerializer
    -0.47
     oprot
    -0.47
    StoryboardSegue
    -0.46
    :✨
    -0.45
    contentLoaded
    -0.45
    MergeFrom
    -0.43
     defaultstate
    -0.42
    RenderAtEndOf
    -0.41
     florales
    -0.41
    POSITIVE LOGITS
     pulp
    0.99
     wood
    0.91
     timber
    0.90
     paper
    0.88
     forestry
    0.87
     lumber
    0.86
     Pulp
    0.86
    Pulp
    0.86
     logging
    0.84
     forest
    0.80
    Activations Density 0.069%

    No Known Activations