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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. 2-RES-JB
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    Explanations

    mentions of fast food chains and restaurants

    oai_token-act-pair · gpt-3.5-turbo

    references to fast food restaurants and their menu items

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Subjects
    -0.76
    vernment
    -0.71
    Filename
    -0.71
     fract
    -0.70
     IPCC
    -0.69
     Galile
    -0.68
    åĬ
    -0.66
     Nun
    -0.65
     declass
    -0.65
     nep
    -0.64
    POSITIVE LOGITS
    isine
    0.98
    ecake
    0.96
    ushi
    0.95
    rette
    0.92
    nuts
    0.90
    Cola
    0.90
    Store
    0.90
    stores
    0.88
     Delicious
    0.86
     vending
    0.86
    Activations Density 0.324%

    No Known Activations