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    3. Google DeepMind · Exploring Gemma 2 with Gemma Scope
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    Explanations

    words and terms related to "pro" or "pro-" prefixes, indicating various concepts in biomedical and scientific contexts

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

    scientific or medical terminology, particularly prefixes like "pro-" used in medical and scientific contexts.

    oai_token-act-pair · claude-3-5-haiku-20241022Triggered by @neilrathi

    The neuron detects words with the prefix "pro" such as "protein", "proline", "promoting", "prophylaxis", "provocation", and "prolonged".

    oai_token-act-pair · claude-3-7-sonnet-20250219Triggered by @neilrathi
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B @ 20-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-pt-res/layer_20/width_16k/average_l0_68
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.20.hook_resid_post
    Hook Layer
    20
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    anças
    -0.52
    onedDateTime
    -0.52
     médié
    -0.51
    Needle
    -0.51
     telefónica
    -0.50
     sieci
    -0.50
     GetUser
    -0.49
    𝕫
    -0.48
    المناصب
    -0.48
     matahari
    -0.47
    POSITIVE LOGITS
     Pro
    0.76
     PRO
    0.75
     pro
    0.74
    PRO
    0.69
    Pro
    0.69
    pro
    0.69
    opro
    0.63
     p
    0.61
     про
    0.60
     Prou
    0.59
    Activations Density 0.270%

    No Known Activations