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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. 1-RES-JB
    11. 13002
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    INDEX
    Explanations

    numerical values related to attendance or enrollment

    oai_token-act-pair · gpt-3.5-turbo

    terms related to attendance statistics or participation numbers

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ofi
    -0.73
    Tes
    -0.72
    bern
    -0.69
     schizophren
    -0.68
    ber
    -0.65
     bipolar
    -0.64
    RA
    -0.64
    itars
    -0.61
     biologically
    -0.61
     existential
    -0.61
    POSITIVE LOGITS
     attendance
    1.40
     Attend
    1.19
    enance
    0.90
     attendees
    0.85
     attend
    0.84
    oided
    0.76
     screenings
    0.74
     visits
    0.74
     tickets
    0.72
     attends
    0.72
    Activations Density 0.007%

    No Known Activations