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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 2-RES-JB
    11. 1685
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    Explanations

    words related to competition, specifically focusing on winners and losers

    oai_token-act-pair · gpt-3.5-turbo

    terms related to winners and losers in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ERA
    -0.75
    avia
    -0.75
    rients
    -0.66
    QU
    -0.64
    rises
    -0.64
    lished
    -0.63
    cially
    -0.63
    ña
    -0.62
    into
    -0.61
    Ec
    -0.60
    POSITIVE LOGITS
     loser
    1.34
     losers
    1.32
     forfeit
    0.75
    igue
    0.74
     contestant
    0.73
     winners
    0.71
    abama
    0.70
     vict
    0.69
    oldemort
    0.69
     prize
    0.68
    Activations Density 0.006%

    No Known Activations