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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. 3-RES-JB
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    Explanations

    terms related to being alert and watchful for potential danger or threats

    oai_token-act-pair · gpt-3.5-turbo

    terms related to vigilance and vigilantism

    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
    #$#$
    -0.80
    fixed
    -0.79
    HF
    -0.77
    cloth
    -0.74
    WAY
    -0.73
    MER
    -0.71
    Commerce
    -0.71
    bid
    -0.71
    ffen
    -0.69
    board
    -0.69
    POSITIVE LOGITS
     vigilant
    1.06
     vigilance
    0.88
    igil
    0.84
    illance
    0.81
    iously
    0.80
    ignt
    0.80
    urnal
    0.77
    ively
    0.75
    ante
    0.74
     vigilante
    0.73
    Activations Density 0.010%

    No Known Activations