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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
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    Explanations

    specific mentions of sports conferences

    oai_token-act-pair · gpt-3.5-turbo

    references to sports conferences

    oai_token-act-pair · gpt-4o-mini
    Triggered 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
    Negative Logits
    irit
    -0.83
    tm
    -0.74
    Ly
    -0.73
    terday
    -0.72
    sym
    -0.72
    response
    -0.71
    haar
    -0.68
    har
    -0.68
    tar
    -0.68
    bur
    -0.67
    POSITIVE LOGITS
     standings
    1.19
     playoffs
    1.07
     Finals
    1.00
     championships
    0.99
     championship
    0.98
     playoff
    0.98
     Playoffs
    0.93
     matchups
    0.91
     Playoff
    0.90
     leagues
    0.85
    Activations Density 0.045%

    No Known Activations