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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. 19
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    Explanations

    words related to emphasizing or stressing a point

    oai_token-act-pair · gpt-3.5-turbo

    words related to emphasizing or highlighting important points

    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
    advertising
    -0.74
    onew
    -0.73
    busters
    -0.71
    ettes
    -0.67
    pedia
    -0.66
    sil
    -0.65
    iop
    -0.65
    found
    -0.65
    abases
    -0.65
    Beck
    -0.63
    POSITIVE LOGITS
    xual
    0.89
     emphasizing
    0.85
     emphasizes
    0.80
     stresses
    0.78
     emphasize
    0.78
     shifts
    0.76
     emphasized
    0.75
     emphas
    0.73
     contrasts
    0.73
     emphasis
    0.71
    Activations Density 0.016%

    No Known Activations