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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. 10015
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    Explanations

    statistics and data related to sports performance

    oai_token-act-pair · gpt-3.5-turbo

    statistical data related to sports performance metrics

    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
    ophon
    -0.75
    idav
    -0.75
    enegger
    -0.70
    reprene
    -0.68
    eln
    -0.67
    opian
    -0.66
     Portug
    -0.66
     testim
    -0.65
     concess
    -0.64
    kid
    -0.62
    POSITIVE LOGITS
     turnovers
    1.13
     offense
    1.03
     touchdowns
    0.97
     turnover
    0.94
     scrimmage
    0.92
     Offense
    0.91
     defense
    0.87
     halftime
    0.86
     offenses
    0.86
     touchdown
    0.85
    Activations Density 0.214%

    No Known Activations