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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. 7-RES-JB
    11. 3601
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    Explanations

    words related to event attendance or participation

    oai_token-act-pair · gpt-3.5-turbo

    metrics related to attendance and turnout

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    enthal
    -0.68
    olog
    -0.67
    grave
    -0.65
    pex
    -0.65
    imb
    -0.63
    thodox
    -0.62
    ishop
    -0.62
    iche
    -0.60
     shepherd
    -0.58
    thur
    -0.58
    POSITIVE LOGITS
     attendance
    0.84
     Attend
    0.84
     turnout
    0.72
    enance
    0.71
    bands
    0.70
     rates
    0.68
     tickets
    0.67
     Tickets
    0.67
    ticket
    0.66
     rate
    0.66
    Activations Density 0.049%

    No Known Activations