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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. 21129
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    INDEX
    Explanations

    instances where emphasis or importance is being placed on a specific concept or idea

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "emphasize" and its variations

    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
    nex
    -0.76
    sil
    -0.73
    amia
    -0.70
    izons
    -0.67
    dr
    -0.66
    irl
    -0.66
    thur
    -0.66
    install
    -0.64
    onew
    -0.62
    load
    -0.62
    POSITIVE LOGITS
     emphasizing
    1.08
     emphasized
    1.01
     emphasizes
    0.97
     emphasize
    0.92
    xual
    0.88
     emphas
    0.85
     contrasts
    0.85
     emphasis
    0.82
     stressing
    0.81
     misunder
    0.79
    Activations Density 0.016%

    No Known Activations