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    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
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    Explanations

    references to transportation and logistics, specifically regarding shipments and deliveries

    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
    447
    +0.24
    1.0%
    639
    +0.12
    0.5%
    220
    +0.11
    0.5%
    Correlated Neurons
    Index
    P. Corr.
    Cos Sim.
    639
    +0.24
    0.13
    529
    +0.12
    0.09
    368
    +0.11
    0.12
    Negative Logits
    ĪĴ
    -0.74
     Pom
    -0.70
     Mayo
    -0.69
     tremend
    -0.68
     Shine
    -0.67
    ellen
    -0.66
    nah
    -0.66
     Moreno
    -0.65
     complexion
    -0.65
     Guth
    -0.64
    POSITIVE LOGITS
     shipments
    1.10
     deliveries
    1.01
     shipment
    0.98
     goods
    0.96
    export
    0.95
     transporting
    0.94
    loads
    0.92
     exports
    0.89
     smuggled
    0.88
     convoy
    0.86
    Activations Density 19.088%

    No Known Activations