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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. 23228
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    Explanations

    phrases related to maximizing potential or efficiency

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating maximizing or extracting value

    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
    ilers
    -0.70
    interstitial
    -0.63
     millenn
    -0.61
    adows
    -0.60
    iterranean
    -0.56
     Inqu
    -0.56
     Gadget
    -0.55
    avorite
    -0.54
     book
    -0.54
    jriwal
    -0.54
    POSITIVE LOGITS
    ta
    1.23
    wards
    1.05
    bur
    0.90
    smart
    0.88
    standing
    0.83
    fitted
    0.82
     of
    0.82
    lier
    0.80
     loud
    0.80
    casts
    0.79
    Activations Density 0.073%

    No Known Activations