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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. 9403
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    Explanations

    data related to sports games performance

    oai_token-act-pair · gpt-3.5-turbo

    references to the number of games played in a sports context

    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
     politic
    -0.84
    sie
    -0.70
    ract
    -0.68
    asin
    -0.68
    yg
    -0.67
    xon
    -0.66
    eous
    -0.65
    Else
    -0.63
     manif
    -0.62
    actor
    -0.62
    POSITIVE LOGITS
    manship
    0.91
     Played
    0.82
    poons
    0.82
    erver
    0.80
     games
    0.78
    士
    0.77
     played
    0.75
    AMES
    0.75
    OTA
    0.74
     expectancy
    0.71
    Activations Density 0.033%

    No Known Activations