© Neuronpedia 2026
    Privacy & TermsBlogGitHubSlackTwitterContact
    Neuronpedia logo - a computer chip with a rounded viewfinder border around it

    Neuronpedia

    Natural Language
    Autoencoders
    NEW    Assistant AxisNEWCircuit TracerUPDATESteerSAE EvalsExportsAPI Community BlogPrivacy & TermsContact
    1. Home
    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
    5. Gemma-2-9B
    7. Residual Stream - 16k
    9. 31-GEMMASCOPE-RES-16K
    11. 13596
    Prev
    Next
    INDEX
    Explanations

    modal verbs and their usage in sentences

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

    German auxiliary and modal verbs (such as haben, sein, können, müssen, wollen, dürfen, sollen, hätte).

    oai_token-act-pair · claude-4-5-haikuTriggered by @emiglarou
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 31-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_31/width_16k/average_l0_114
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    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
    GEBURTSDATUM
    -0.95
    ScopeManager
    -0.73
     ویکی‌پدی
    -0.70
    CppMethod
    -0.69
     AspNetCore
    -0.68
    niſſe
    -0.68
    ſicht
    -0.67
    URBANA
    -0.66
     queſta
    -0.66
    Chham
    -0.65
    POSITIVE LOGITS
     indeed
    0.52
     nevertheless
    0.45
     البته
    0.44
     also
    0.43
     unfortunately
    0.41
     already
    0.40
     however
    0.39
     meanwhile
    0.38
     nemlig
    0.37
     totiž
    0.37
    Activations Density 0.094%

    No Known Activations