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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. 8-RES-JB
    11. 5084
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    Explanations

    relevant statistics in a sports context

    oai_token-act-pair · gpt-3.5-turbo

    numerical statistics 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 @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    phant
    -0.68
    insula
    -0.66
    agine
    -0.65
    peak
    -0.62
    netflix
    -0.62
    zos
    -0.62
    onym
    -0.61
    orc
    -0.61
     Rao
    -0.61
    igm
    -0.61
    POSITIVE LOGITS
     possessions
    0.97
     stitches
    0.91
    %,
    0.91
     mph
    0.91
     yards
    0.90
     Minutes
    0.89
     assists
    0.89
    %
    0.88
    %-
    0.88
     pts
    0.88
    Activations Density 0.185%

    No Known Activations