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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. 9576
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    INDEX
    Explanations

    the word "want" at various levels of intensity

    oai_token-act-pair · gpt-3.5-turbo

    expressions of desire or intention

    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
    VERTISEMENT
    -0.67
    dor
    -0.66
    grim
    -0.66
    uum
    -0.65
    vision
    -0.63
    ammy
    -0.63
     Echoes
    -0.63
    ricks
    -0.62
    errors
    -0.62
    voy
    -0.61
    POSITIVE LOGITS
    urities
    0.78
     to
    0.75
    uld
    0.66
     mate
    0.65
    nels
    0.64
     him
    0.63
    reprene
    0.62
     quotas
    0.61
    htar
    0.61
    FontSize
    0.61
    Activations Density 0.077%

    No Known Activations