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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. 3-RES-JB
    11. 8755
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    INDEX
    Explanations

    adjectives describing a process as laborious or detail-oriented

    oai_token-act-pair · gpt-3.5-turbo

    words related to careful or labor-intensive efforts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    entin
    -0.78
     Panc
    -0.71
    stocks
    -0.71
    idas
    -0.71
    mbuds
    -0.69
    azine
    -0.67
    ENCE
    -0.67
    lik
    -0.66
    Fram
    -0.66
     References
    -0.64
    POSITIVE LOGITS
     painstaking
    1.01
     tedious
    0.91
     detail
    0.83
     meticulous
    0.81
     ardu
    0.80
     grind
    0.80
    staking
    0.78
     diligently
    0.75
    consuming
    0.74
     exped
    0.72
    Activations Density 0.046%

    No Known Activations