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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 6-RES-JB
    6. 16765
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    Explanations

    references to cereal boxes

    oai_token-act-pair · gpt-3.5-turbo

    references to cereal and related food items

    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
    sein
    -0.81
    etter
    -0.77
    handled
    -0.75
    angs
    -0.72
    essing
    -0.70
     tremend
    -0.68
    ĺħ
    -0.68
    liness
    -0.68
    fully
    -0.67
    finding
    -0.67
    POSITIVE LOGITS
     Stout
    0.76
    alore
    0.76
     NAD
    0.75
    mil
    0.73
    FACE
    0.73
    llo
    0.72
     Milk
    0.72
     cere
    0.71
    AAF
    0.71
     milk
    0.70
    Activations Density 0.045%

    No Known Activations