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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. 18116
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    Explanations

    statements describing objectives or purposes of different projects or actions

    oai_token-act-pair · gpt-3.5-turbo

    statements outlining goals or objectives

    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
    oos
    -0.64
    shit
    -0.63
    iery
    -0.63
    osa
    -0.61
    ypes
    -0.60
    gian
    -0.59
    features
    -0.59
    olor
    -0.59
    lasses
    -0.59
    ax
    -0.59
    POSITIVE LOGITS
     maximizing
    0.98
     preservation
    0.85
     ensuring
    0.82
     preserving
    0.80
     restoring
    0.77
     to
    0.77
     protecting
    0.75
     revenge
    0.75
     deterrence
    0.75
     vengeance
    0.73
    Activations Density 0.195%

    No Known Activations