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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 4-RES-JB
    6. 8343
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    Explanations

    keywords related to data analysis, research, and statistical correlations in various topics such as energy consumption, gun ownership, and medical conditions

    oai_token-act-pair · gpt-3.5-turbo

    terms related to resource consumption and usage patterns

    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
    ormal
    -0.74
    IRC
    -0.73
    RET
    -0.68
    ARR
    -0.67
    ofi
    -0.66
    xxxxxxxx
    -0.66
    pher
    -0.66
    endiary
    -0.65
    ERG
    -0.65
    POS
    -0.65
    POSITIVE LOGITS
     habits
    0.86
     disorder
    0.79
     expectancy
    0.73
     disorders
    0.73
     indexes
    0.71
     expenditure
    0.70
     rates
    0.70
     correlates
    0.69
     Ratings
    0.69
     ratings
    0.68
    Activations Density 0.294%

    No Known Activations