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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
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    Explanations

    terms related to sports matches ending in a draw

    oai_token-act-pair · gpt-3.5-turbo

    instances of the word "draw" and its variations, indicating a focus on tied or evenly matched outcomes, particularly in sports contexts

    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
    nown
    -1.04
    anamo
    -0.87
     srf
    -0.81
     bom
    -0.80
    wagen
    -0.77
    cffffcc
    -0.77
    ternity
    -0.76
    userc
    -0.75
    illon
    -0.73
    esta
    -0.72
    POSITIVE LOGITS
    draw
    0.90
    cards
    0.90
     draw
    0.88
     Draw
    0.86
    card
    0.86
    backs
    0.86
     drawn
    0.83
     Drawn
    0.80
     draws
    0.79
    downs
    0.76
    Activations Density 0.012%

    No Known Activations