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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    7. Residual Stream
    9. 3-RES-JB
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    Explanations

    references to theft and related criminal activities

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "theft" and related terminology

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    enegger
    -0.84
    shr
    -0.75
    imposed
    -0.72
    present
    -0.72
    astical
    -0.71
    IX
    -0.70
    travel
    -0.69
    nant
    -0.66
    tem
    -0.65
    ennett
    -0.64
    POSITIVE LOGITS
     Theft
    0.99
     spree
    0.93
     theft
    0.88
     thefts
    0.83
     unfocusedRange
    0.79
    æ©
    0.73
     stealing
    0.71
     thief
    0.71
     robbery
    0.71
     stolen
    0.71
    Activations Density 0.014%

    No Known Activations