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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. 10-RES-JB
    11. 6314
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    Explanations

    sport-related phrases or statistics, particularly about teams and their performance

    oai_token-act-pair · gpt-3.5-turbo

    references to sports teams and their performances

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     concess
    -0.98
     involuntary
    -0.85
    untary
    -0.82
     coerc
    -0.81
     perspect
    -0.81
     commissions
    -0.79
     impulse
    -0.76
     facult
    -0.76
     polymorph
    -0.75
     volunt
    -0.74
    POSITIVE LOGITS
    Their
    1.15
     Their
    1.13
     They
    1.09
     Pittsburgh
    1.03
    They
    1.02
     Cincinnati
    1.00
     Denver
    0.98
     Jacksonville
    0.97
     Playoff
    0.97
     Miami
    0.97
    Activations Density 0.364%

    No Known Activations