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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. 6-RES-JB
    11. 7619
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    Explanations

    phrases indicating attention or focus directed towards something in a critical way

    oai_token-act-pair · gpt-3.5-turbo

    words related to attention and capturing interest

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    times
    -0.68
    apo
    -0.68
    ells
    -0.66
    rived
    -0.66
     Waste
    -0.65
    origin
    -0.63
    ovi
    -0.63
    ambo
    -0.62
     apes
    -0.62
     spaghetti
    -0.61
    POSITIVE LOGITS
    çİĭ
    0.78
     largeDownload
    0.77
     seriously
    0.72
    rogens
    0.70
     respons
    0.64
    kef
    0.64
    mans
    0.64
    ç
    0.62
    erto
    0.60
    teenth
    0.59
    Activations Density 0.075%

    No Known Activations