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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. 20753
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    Explanations

    statistical measures related to sports performance, specifically focusing on yards gained, carries, and touchdowns

    oai_token-act-pair · gpt-3.5-turbo

    statistics and numerical data related to sports 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
     Poster
    -0.70
     Spiegel
    -0.69
    bottom
    -0.69
     Parties
    -0.66
    sych
    -0.65
     Enterprises
    -0.65
     Instruments
    -0.64
    roma
    -0.64
    enegger
    -0.63
    abeth
    -0.63
    POSITIVE LOGITS
     yards
    1.13
    lbs
    1.02
     pounds
    1.01
     lbs
    1.00
     rushing
    0.98
     mph
    0.95
     scrimmage
    0.93
     miles
    0.92
     innings
    0.88
    mph
    0.87
    Activations Density 0.136%

    No Known Activations