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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. 1-RES-JB
    11. 10343
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    Explanations

    detailed and thorough actions or processes

    oai_token-act-pair · gpt-3.5-turbo

    adjectives describing thoroughness and effort

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    stocks
    -0.69
     constitu
    -0.68
     bets
    -0.67
    switch
    -0.66
    azine
    -0.64
     Franch
    -0.62
     Parad
    -0.62
    ozo
    -0.61
    facing
    -0.60
    gate
    -0.60
    POSITIVE LOGITS
     painstaking
    1.19
     meticulous
    1.11
     diligently
    1.01
     meticulously
    0.99
     diligent
    0.81
     grind
    0.79
     exhaustive
    0.78
    teness
    0.77
    ãĥ¯ãĥ³
    0.77
    chy
    0.77
    Activations Density 0.021%

    No Known Activations