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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

    instances of the word "Burger."

    oai_token-act-pair · gpt-3.5-turbo

    mentions of fast food chains and their associated brands

    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
    icter
    -0.91
     downt
    -0.85
    umbn
    -0.78
    resh
    -0.74
    orate
    -0.72
    oral
    -0.71
     migr
    -0.70
    ebin
    -0.69
     Emin
    -0.68
     spirited
    -0.67
    POSITIVE LOGITS
     Burger
    1.04
    Cola
    0.95
     Restaur
    0.95
     Wendy
    0.90
    yu
    0.83
     Brands
    0.82
    loo
    0.78
     Meal
    0.77
     Pizza
    0.76
     Restaurant
    0.76
    Activations Density 0.017%

    No Known Activations