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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. 243
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    Explanations

    mentions of winners

    oai_token-act-pair · gpt-3.5-turbo

    references to the concept of a "winner" in various contexts

    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
    uli
    -0.82
     sulf
    -0.70
    ugu
    -0.68
    uku
    -0.66
    uld
    -0.66
    estation
    -0.65
    aeda
    -0.65
    rients
    -0.65
    emetery
    -0.64
    senal
    -0.64
    POSITIVE LOGITS
     winner
    0.93
     Winner
    0.90
    Winner
    0.88
     winners
    0.78
     contestant
    0.77
    athon
    0.74
     prize
    0.72
     laureate
    0.71
     loser
    0.71
     Hugo
    0.70
    Activations Density 0.015%

    No Known Activations