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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
    11. 22032
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    Explanations

    references to the American football team "Bears"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the Chicago Bears

    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
    employment
    -0.80
    oppable
    -0.74
    asive
    -0.74
    ascular
    -0.73
    iltration
    -0.72
    istry
    -0.70
    ADRA
    -0.70
    egal
    -0.69
    akuya
    -0.69
    icate
    -0.66
    POSITIVE LOGITS
     Bears
    1.26
     Tribune
    0.85
     Packers
    0.83
     Bryant
    0.80
     Grizz
    0.79
    downs
    0.77
     Cubs
    0.76
    gans
    0.75
     Slay
    0.74
     Reloaded
    0.73
    Activations Density 0.010%

    No Known Activations