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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 7-RES-JB
    11. 1944
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    Explanations

    words related to negative events or situations, particularly ones involving harm or loss

    oai_token-act-pair · gpt-3.5-turbo

    terms related to death and significant departures

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    vier
    -0.74
    enegger
    -0.73
    Cola
    -0.72
    cale
    -0.72
    isine
    -0.69
    zzy
    -0.67
    igmatic
    -0.63
    ingo
    -0.63
    ocaly
    -0.63
    overe
    -0.62
    POSITIVE LOGITS
     of
    0.94
     thereof
    0.92
     OF
    0.66
     Flavoring
    0.65
     deadline
    0.61
    lights
    0.60
    switch
    0.60
     portion
    0.59
     shuffle
    0.59
    ritz
    0.58
    Activations Density 0.198%

    No Known Activations