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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. 3-RES-JB
    11. 8854
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    Explanations

    numerical values indicating statistics, such as points scored or yards gained, in a sports-related 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 @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ei
    -0.74
    zos
    -0.73
    hran
    -0.72
    uran
    -0.68
    loo
    -0.68
    rex
    -0.67
     guiActiveUn
    -0.67
    cult
    -0.66
    mining
    -0.66
    aran
    -0.65
    POSITIVE LOGITS
     consecutive
    1.01
     preseason
    1.00
     outfield
    1.00
     playoff
    1.00
     postseason
    0.96
     seasons
    0.94
     rookie
    0.92
     Playoffs
    0.91
     Rookie
    0.90
     NBA
    0.90
    Activations Density 0.266%

    No Known Activations