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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. 0-RES-JB
    6. 8493
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    INDEX
    Explanations

    phrases indicating a large quantity or proportion

    oai_token-act-pair · gpt-3.5-turbo

    phrases emphasizing the frequency and magnitude of occurrences

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Ec
    -0.66
    î
    -0.64
    esc
    -0.63
    ÃĽ
    -0.62
    Sy
    -0.61
    ¶æ
    -0.60
     persu
    -0.60
     forwards
    -0.59
    ety
    -0.59
    eteen
    -0.59
    POSITIVE LOGITS
     LOT
    3.04
     disproportionate
    1.90
     lot
    1.56
     disproportionately
    1.52
    lot
    1.35
     Lot
    1.14
    Lot
    1.11
     tremendous
    1.09
    little
    1.07
     alot
    1.06
    Activations Density 0.016%

    No Known Activations