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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. 11-RES-JB
    11. 13148
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    Explanations

    mentions of specific meal times, particularly lunch

    oai_token-act-pair · gpt-3.5-turbo

    references to meals, particularly lunch and dinner

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     Judd
    -0.61
     Laboratory
    -0.60
     braking
    -0.60
    ioxide
    -0.59
    ados
    -0.59
     Ey
    -0.59
    esty
    -0.58
     Jed
    -0.58
     Exile
    -0.57
    ensen
    -0.57
    POSITIVE LOGITS
     buffet
    1.16
    time
    1.14
    worms
    1.02
    table
    1.01
    bowl
    1.00
     meal
    0.97
    winner
    0.95
     menus
    0.92
     menu
    0.92
    menu
    0.91
    Activations Density 0.071%

    No Known Activations