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

    references to public transportation systems

    oai_token-act-pair · gpt-3.5-turbo

    mentions of public transit systems, particularly the TTC (Toronto Transit Commission)

    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
    orgetown
    -0.88
    yer
    -0.74
    croft
    -0.72
     Williamson
    -0.70
    gew
    -0.68
    cius
    -0.67
    lies
    -0.66
     Hindu
    -0.66
    áµ
    -0.66
    hunter
    -0.66
    POSITIVE LOGITS
    TY
    0.85
     MTA
    0.84
    acco
    0.83
    PA
    0.79
    CCC
    0.78
     TTC
    0.77
     timet
    0.75
     fare
    0.74
     commute
    0.73
     rail
    0.72
    Activations Density 0.008%

    No Known Activations