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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. 1-RES-JB
    6. 18180
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    INDEX
    Explanations

    words related to items associated with dining or eating, specifically identifying napkins

    oai_token-act-pair · gpt-3.5-turbo

    references to napkins

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Mand
    -0.75
    ²¾
    -0.75
    ourke
    -0.73
    leys
    -0.72
    Relations
    -0.71
    Chance
    -0.68
    ley
    -0.68
    RAY
    -0.67
    lev
    -0.66
    ×Ļ×
    -0.66
    POSITIVE LOGITS
    oleon
    1.43
     nap
    1.30
    puter
    0.89
    edia
    0.86
    olitan
    0.79
    anqu
    0.79
    olicy
    0.78
    ublic
    0.78
    eday
    0.77
     pav
    0.75
    Activations Density 0.011%

    No Known Activations