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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 1656
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    INDEX
    Explanations

    mentions of winners or winning in competitive contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to "winner" in various contexts, particularly in competitive scenarios

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    uli
    -0.72
    otrop
    -0.70
     sulf
    -0.69
    rir
    -0.68
    Ku
    -0.65
    ohyd
    -0.62
     Gau
    -0.62
    rients
    -0.62
    otropic
    -0.61
    allel
    -0.60
    POSITIVE LOGITS
     winner
    1.04
     winners
    0.97
     contestant
    0.94
     prizes
    0.90
     contender
    0.85
     losers
    0.84
     loser
    0.83
     prize
    0.82
    Winner
    0.80
     contenders
    0.79
    Activations Density 0.045%

    No Known Activations