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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

    mentions of attendance or attendees in various contexts

    oai_token-act-pair · gpt-3.5-turbo

    words and phrases associated with attendance at events

    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
    grave
    -0.71
    ofi
    -0.68
    geon
    -0.65
    itars
    -0.63
    enthal
    -0.62
    enegger
    -0.62
     schizophren
    -0.60
     poetic
    -0.60
    imb
    -0.60
    Tes
    -0.59
    POSITIVE LOGITS
     attendance
    1.10
     Attend
    1.08
     attendees
    0.84
     attend
    0.82
    enance
    0.75
     attends
    0.73
     Tickets
    0.73
    oided
    0.72
     screenings
    0.70
     Ticket
    0.69
    Activations Density 0.015%

    No Known Activations