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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. 20449
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    Explanations

    words or phrases related to sports plays or strategies, specifically focusing on players lining up in a certain position

    oai_token-act-pair · gpt-3.5-turbo

    instances of the phrase "lined up" or variations thereof

    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
    >"
    -0.69
     Musk
    -0.66
     largeDownload
    -0.63
     Mole
    -0.62
    orem
    -0.59
     [/
    -0.59
    [/
    -0.58
     perv
    -0.57
     Canary
    -0.57
     Paraly
    -0.56
    POSITIVE LOGITS
    stairs
    0.94
    dates
    0.86
    river
    0.81
    tics
    0.76
    roots
    0.74
    ansas
    0.74
    olicy
    0.73
    adesh
    0.72
    atches
    0.72
    Ü
    0.71
    Activations Density 0.094%

    No Known Activations