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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 6675
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    INDEX
    Explanations

    names of individuals

    oai_token-act-pair · gpt-3.5-turbo

    mentions of athletes and their statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Columb
    -0.73
    riet
    -0.71
     Dorothy
    -0.69
     Gloria
    -0.69
    sylv
    -0.68
     Laurel
    -0.67
     Wendy
    -0.66
     censor
    -0.66
    edition
    -0.65
     Duchess
    -0.64
    POSITIVE LOGITS
     underwent
    1.03
     averaged
    1.01
     accrued
    1.00
     exce
    1.00
    signed
    0.99
     versatility
    0.97
     undrafted
    0.96
     teammates
    0.95
     struggled
    0.94
     waived
    0.93
    Activations Density 0.438%

    No Known Activations