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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. 4-RES-JB
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    Explanations

    the word "attractive" with various intensities

    oai_token-act-pair · gpt-3.5-turbo

    mentions of attractiveness in various contexts

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

    No Comments

    Negative Logits
    cedented
    -0.86
    othe
    -0.77
    roman
    -0.74
    avis
    -0.71
    çīĪ
    -0.70
    jer
    -0.69
    FIN
    -0.69
    Ber
    -0.68
    iche
    -0.68
    ignt
    -0.66
    POSITIVE LOGITS
     attractive
    0.94
     lure
    0.88
     proposition
    0.86
     attractiveness
    0.85
    lihood
    0.82
     propositions
    0.75
     enticing
    0.75
     attract
    0.72
     attracts
    0.72
     contests
    0.72
    Activations Density 0.015%

    No Known Activations