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

    mentions of the sport "football"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of football

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    EStream
    -0.83
    utter
    -0.78
     Ples
    -0.72
    UTC
    -0.68
    REM
    -0.66
     Nas
    -0.66
    70710
    -0.63
    semble
    -0.63
    quart
    -0.62
    PsyNetMessage
    -0.62
    POSITIVE LOGITS
     stadiums
    0.88
     football
    0.85
    matically
    0.83
     clubs
    0.81
     fraternity
    0.78
     scholarships
    0.77
    club
    0.77
     club
    0.76
    sburg
    0.75
     Clubs
    0.74
    Activations Density 0.018%

    No Known Activations