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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. 5-RES-JB
    6. 793
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    INDEX
    Explanations

    mentions of daily activities or routines

    oai_token-act-pair · gpt-3.5-turbo

    references to daily routines or practices

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    holes
    -0.96
    essee
    -0.88
    atchewan
    -0.78
     Gould
    -0.77
    artisan
    -0.76
    hole
    -0.75
    aine
    -0.74
    OHN
    -0.73
    eer
    -0.72
    erala
    -0.72
    POSITIVE LOGITS
    motion
    1.03
     occurrence
    0.92
     commute
    0.86
     ration
    0.82
     intervals
    0.81
     basis
    0.80
     cycle
    0.79
     routines
    0.79
     thereafter
    0.79
     occurrences
    0.78
    Activations Density 0.018%

    No Known Activations