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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. 9-RES-JB
    11. 16535
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    Explanations

    specific numerical data, such as numbers or statistics

    oai_token-act-pair · gpt-3.5-turbo

    the word "in" as it relates to various contexts and statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    !--
    -0.71
    agine
    -0.70
     fate
    -0.69
    UV
    -0.68
     contam
    -0.68
     intensify
    -0.66
     sparing
    -0.65
    estinal
    -0.64
    .$
    -0.64
     tremend
    -0.64
    POSITIVE LOGITS
     parentheses
    0.91
     OECD
    0.90
     Percent
    0.78
     2010
    0.76
     2011
    0.74
     2009
    0.73
     2013
    0.73
     each
    0.73
     2014
    0.71
     2007
    0.70
    Activations Density 0.229%

    No Known Activations