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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. 2546
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    Explanations

    references to running marathons, marathon events, and related activities

    oai_token-act-pair · gpt-3.5-turbo

    references to the Boston Marathon

    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
    orum
    -0.82
    tics
    -0.75
    olia
    -0.73
    metics
    -0.72
     suscept
    -0.69
    imated
    -0.69
    under
    -0.68
    oshop
    -0.67
    erie
    -0.65
    otle
    -0.64
    POSITIVE LOGITS
     runner
    1.07
     Runner
    0.98
     marathon
    0.96
     runners
    0.90
    athon
    0.89
     Marathon
    0.88
    NING
    0.78
     bombings
    0.77
     bombing
    0.76
     Polo
    0.76
    Activations Density 0.013%

    No Known Activations