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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. 17906
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    INDEX
    Explanations

    words related to optics or vision

    oai_token-act-pair · gpt-3.5-turbo

    mention of lenses, particularly in a metaphorical or literal sense

    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
    lly
    -0.80
    BY
    -0.75
    anqu
    -0.72
    TY
    -0.68
    onge
    -0.68
    avez
    -0.67
    icted
    -0.66
    alky
    -0.66
     Chatt
    -0.66
     Carnegie
    -0.64
    POSITIVE LOGITS
     lens
    1.14
     flares
    1.10
     lenses
    1.09
     flare
    1.02
     Lens
    0.93
     aperture
    0.83
    linger
    0.83
    Lens
    0.82
    horn
    0.80
     Mechdragon
    0.79
    Activations Density 0.013%

    No Known Activations