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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
    11. 16104
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    Explanations

    words related to specific physical objects or structures, specifically the word "liner"

    oai_token-act-pair · gpt-3.5-turbo

    terminology related to ship liners and seams

    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
    inction
    -0.75
    arta
    -0.69
    Ĥª
    -0.69
    hma
    -0.64
    stood
    -0.63
    ortion
    -0.62
    rament
    -0.61
    ummies
    -0.61
    hered
    -0.61
    anooga
    -0.60
    POSITIVE LOGITS
     liner
    1.14
     lin
    0.75
    backer
    0.74
    early
    0.70
    ibrary
    0.68
    anuts
    0.67
     embell
    0.67
    ascript
    0.66
     sheet
    0.66
    ptin
    0.65
    Activations Density 0.013%

    No Known Activations