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

    the word "participants"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of participants in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    strip
    -0.69
    bar
    -0.66
    agar
    -0.66
    hunt
    -0.65
    oute
    -0.65
    brush
    -0.64
    thora
    -0.62
    bane
    -0.61
    ray
    -0.60
     whine
    -0.60
    POSITIVE LOGITS
     participants
    3.56
     Participants
    2.89
     participant
    2.81
     attendees
    2.34
    Particip
    2.24
    particip
    1.98
     entrants
    1.94
     contestants
    1.93
     respondents
    1.85
     Participant
    1.81
    Activations Density 0.018%

    No Known Activations