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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. 2318
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    Explanations

    phrases related to driving forces or motivations

    oai_token-act-pair · gpt-3.5-turbo

    phrases that indicate causation or motivation

    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
    enegger
    -0.71
     vantage
    -0.66
    antage
    -0.64
     pads
    -0.64
     Kinnikuman
    -0.64
    akings
    -0.64
    eport
    -0.63
     Canad
    -0.63
    umbn
    -0.62
    alon
    -0.61
    POSITIVE LOGITS
     by
    0.95
     BY
    0.90
    by
    0.88
    Ń·
    0.81
     solely
    0.80
     principally
    0.77
    By
    0.76
     aback
    0.75
     By
    0.74
     destro
    0.73
    Activations Density 0.154%

    No Known Activations