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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. 0-RES-JB
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    Explanations

    references to athletic events, teams or organizations

    oai_token-act-pair · gpt-3.5-turbo

    terms related to athletics and athletic events

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     collateral
    -0.85
     meta
    -0.72
     hash
    -0.71
     Meta
    -0.69
     Loot
    -0.68
    spawn
    -0.66
     taco
    -0.65
    iable
    -0.65
     spawn
    -0.64
    typ
    -0.64
    POSITIVE LOGITS
     Athletics
    3.50
     athletics
    3.28
     athlet
    1.47
    athlon
    1.36
     Athletic
    1.20
     athletic
    1.08
    asketball
    1.06
    basketball
    0.99
     gymn
    0.96
    Sports
    0.93
    Activations Density 0.052%

    No Known Activations