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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. 8636
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    INDEX
    Explanations

    mentions of sports teams and their performance

    oai_token-act-pair · gpt-3.5-turbo

    statements about sports teams and their performance

    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
     concess
    -0.99
     mascul
    -0.88
     perspect
    -0.88
     pseud
    -0.88
     solicitor
    -0.86
     commissions
    -0.86
     authorised
    -0.85
     volunt
    -0.85
     advoc
    -0.83
     ministerial
    -0.83
    POSITIVE LOGITS
     Playoff
    1.25
     Teams
    1.17
     Winning
    1.06
     Players
    1.06
     Coach
    1.04
     Fans
    1.02
     Jacksonville
    1.02
     Atlanta
    1.00
     Pittsburgh
    0.97
     Derrick
    0.96
    Activations Density 0.517%

    No Known Activations