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

    mentions of political election outcomes

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "won" and related victory terms in the context of political competition

    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
    Root
    -0.70
    MOD
    -0.68
    Else
    -0.68
    hid
    -0.68
    mol
    -0.68
    udes
    -0.67
    atis
    -0.66
    rete
    -0.64
    modules
    -0.63
    Plot
    -0.62
    POSITIVE LOGITS
     reelection
    0.84
     elector
    0.83
    't
    0.78
    election
    0.76
     elections
    0.76
     voter
    0.75
     victories
    0.74
     votes
    0.74
     majorities
    0.74
     Republican
    0.72
    Activations Density 0.047%

    No Known Activations