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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. 1-RES-JB
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    Explanations

    mentions of the word "Win" followed by a numerical value or description

    oai_token-act-pair · gpt-3.5-turbo

    references to the term "Win" in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Uz
    -0.76
    âĶģ
    -0.72
     condu
    -0.72
    ateral
    -0.71
    orescent
    -0.70
    terday
    -0.69
     unexplained
    -0.67
     unnecess
    -0.66
    ilitary
    -0.65
    xual
    -0.65
    POSITIVE LOGITS
    ners
    1.18
    win
    1.08
    frey
    0.96
    fred
    0.94
     Win
    0.92
    Win
    0.87
    ning
    0.87
    kees
    0.84
    throp
    0.81
    nings
    0.81
    Activations Density 0.007%

    No Known Activations