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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. 10-RES-JB
    11. 5745
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    Explanations

    statistics related to points and rebounds in sports contexts

    oai_token-act-pair · gpt-3.5-turbo

    quantitative statistics related to points and rebounds in sports

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     externalToEVAOnly
    -0.73
    oidal
    -0.72
    ays
    -0.65
    ay
    -0.62
    ctors
    -0.62
    ords
    -0.61
    unci
    -0.61
    english
    -0.61
    enegger
    -0.60
     Romeo
    -0.59
    POSITIVE LOGITS
     apiece
    0.88
     scored
    0.86
     blank
    0.77
     streak
    0.74
     scorer
    0.72
     deduction
    0.71
    uable
    0.71
     deducted
    0.71
    reau
    0.70
     finishes
    0.70
    Activations Density 0.031%

    No Known Activations