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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. 8983
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    Explanations

    phrases related to brushing or coating objects or dealing with situations in a casual or cursory manner

    oai_token-act-pair · gpt-3.5-turbo

    references to various types of brushes and the act of brushing

    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
    uthor
    -0.71
     regress
    -0.70
    undai
    -0.66
    infeld
    -0.66
     Mandela
    -0.65
    ukong
    -0.65
    uras
    -0.64
    omething
    -0.63
     Founding
    -0.63
    igmat
    -0.62
    POSITIVE LOGITS
    brush
    1.02
    stroke
    0.95
    stro
    0.93
     brush
    0.92
     strokes
    0.89
     brushes
    0.84
    tip
    0.83
     applic
    0.82
     brist
    0.80
    chery
    0.78
    Activations Density 0.046%

    No Known Activations