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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. 4-RES-JB
    11. 19667
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    Explanations

    numerical quantities, specifically focusing on counts or quantities of people

    oai_token-act-pair · gpt-3.5-turbo

    references to numerical data and statistics

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

    No Comments

    Negative Logits
    axter
    -0.74
    rador
    -0.73
    endon
    -0.69
    umenthal
    -0.66
    aimon
    -0.64
    _-
    -0.64
    INTON
    -0.63
    robe
    -0.62
    missible
    -0.62
     Passage
    -0.61
    POSITIVE LOGITS
    number
    0.94
     number
    0.93
     Numbers
    0.87
     numbers
    0.85
    metry
    0.82
    enance
    0.77
    NUM
    0.76
     666
    0.76
    population
    0.74
     crunch
    0.72
    Activations Density 0.034%

    No Known Activations