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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. 1-RES-JB
    11. 21364
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    Explanations

    expletives conveying strong emphasis

    oai_token-act-pair · gpt-3.5-turbo

    expressions of emphasis or exclamation

    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
    NetMessage
    -1.02
    xes
    -0.73
    PT
    -0.69
     Sapp
    -0.67
    Sample
    -0.67
    x
    -0.66
    externalActionCode
    -0.66
    ramid
    -0.64
    BOOK
    -0.63
    phrine
    -0.62
    POSITIVE LOGITS
     damn
    1.13
     darn
    1.11
     damned
    1.01
    owship
    0.87
    atio
    0.82
    rontal
    0.80
     goddamn
    0.79
     Damn
    0.78
     fucking
    0.74
    ulously
    0.73
    Activations Density 0.007%

    No Known Activations