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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. 9-RES-JB
    6. 20670
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    Explanations

    words related to repetitive patterns or sequences, often involving a series of events or actions that occur in a cyclical manner

    oai_token-act-pair · gpt-3.5-turbo

    references to cycles or cyclical processes

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inez
    -0.95
    orage
    -0.90
    imus
    -0.89
    amina
    -0.82
    essors
    -0.81
    imates
    -0.77
     Aires
    -0.75
    alty
    -0.75
    oaded
    -0.75
    anamo
    -0.73
    POSITIVE LOGITS
     cycle
    0.94
     erg
    0.91
    cycle
    0.83
    cles
    0.83
     repeats
    0.78
     Cycle
    0.74
    chron
    0.74
    dayName
    0.73
     cycles
    0.71
     Delay
    0.71
    Activations Density 0.043%

    No Known Activations