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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. 9-RES-JB
    11. 5830
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    INDEX
    Explanations

    numerical data and details related to team members or participants, particularly in sports contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to sports team compositions and player inclusions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     trillions
    -0.89
     trillion
    -0.83
    agog
    -0.78
     billions
    -0.78
    Enlarge
    -0.77
    FBI
    -0.75
    illions
    -0.74
     Watergate
    -0.69
     Capitalism
    -0.69
     ruin
    -0.68
    POSITIVE LOGITS
     squad
    1.08
     roster
    1.07
     midfielder
    1.01
     squads
    1.01
     rosters
    1.00
    Tickets
    0.94
     undrafted
    0.93
     goalkeeper
    0.91
     newcomers
    0.91
     newcom
    0.91
    Activations Density 0.806%

    No Known Activations