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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. 5-RES-JB
    6. 24364
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    INDEX
    Explanations

    numbers such as scores, points, and statistics in relation to sports

    oai_token-act-pair · gpt-3.5-turbo

    numerical statistics and performance metrics in sports contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    netflix
    -0.71
    zos
    -0.70
    loo
    -0.70
    dor
    -0.69
    oresc
    -0.67
    igm
    -0.66
    actionDate
    -0.66
    mint
    -0.65
    kell
    -0.65
    agine
    -0.63
    POSITIVE LOGITS
    INAL
    0.86
     stitches
    0.84
     consecutive
    0.83
     rookie
    0.82
     FANTASY
    0.79
     injury
    0.79
     mph
    0.78
     injuries
    0.78
     preseason
    0.78
     Defensive
    0.76
    Activations Density 0.166%

    No Known Activations