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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. 6-RES-JB
    11. 1626
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    Explanations

    mentions of meals or eating-related terms

    oai_token-act-pair · gpt-3.5-turbo

    references to meals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ignty
    -0.77
    idency
    -0.70
    inates
    -0.69
     bluff
    -0.66
     Jed
    -0.65
     Moff
    -0.64
    itars
    -0.63
    rity
    -0.60
     Morse
    -0.60
    vernment
    -0.58
    POSITIVE LOGITS
    worms
    1.25
     meal
    1.14
     meals
    1.09
     Meal
    1.06
     eaten
    0.99
     buffet
    0.95
    worm
    0.95
    mares
    0.92
    cloth
    0.84
    meat
    0.81
    Activations Density 0.013%

    No Known Activations