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    1. Home
    2. Apollo Research · Taylor · Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
    3. GPT2-Small
    4. Residual Similar CE Local
    5. 6-RES_SCL-AJT
    6. 33302
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    INDEX
    Explanations

    words related to law enforcement and criminal activity, such as names of drugs, police departments, illegal immigration, and law enforcement actions

    oai_token-act-pair · gpt-3.5-turbo
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    neuronpedia/gpt2-small__res_scl-ajt/6-res_scl-ajt
    Prompts (Dashboard)
    12,288 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    46,080
    Data Type
    torch.float32
    Hook Point
    blocks.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    apollo-research/Skylion007-openwebtext-tokenizer-gpt2
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Neuron Alignment
    Index
    Value
    % of L₁
    663
    +0.02
    0.5%
    757
    +0.01
    0.4%
    208
    +0.01
    0.4%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    640
    +0.02
    0.30
    6
    +0.01
    0.18
    107
    +0.01
    0.06
    Negative Logits
     accur
    -0.11
    ortmund
    -0.10
     arri
    -0.10
    alez
    -0.10
     deprived
    -0.10
    ¥µ
    -0.10
     compr
    -0.10
    ————
    -0.10
     clutter
    -0.10
     Kardash
    -0.09
    POSITIVE LOGITS
    throp
    0.18
    peat
    0.12
    Jet
    0.12
     Swordsman
    0.11
    emort
    0.11
    tails
    0.11
    abal
    0.11
    ortment
    0.11
    ect
    0.10
    tein
    0.10
    Activations Density 16.270%

    No Known Activations