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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. 3-RES-JB
    11. 20794
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    Explanations

    references to monks and monasteries

    oai_token-act-pair · gpt-3.5-turbo

    references to monks and monasteries

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    sg
    -0.74
    ãĥ¤
    -0.72
    Lex
    -0.72
    alez
    -0.71
    Ö¼
    -0.71
    mberg
    -0.69
    女
    -0.68
     NRS
    -0.68
    MET
    -0.67
    BAT
    -0.66
    POSITIVE LOGITS
     monks
    1.09
     monk
    1.04
    mares
    1.00
     monastery
    0.87
     Monk
    0.85
    mare
    0.84
    esses
    0.82
    ajo
    0.81
    itton
    0.74
     robes
    0.73
    Activations Density 0.008%

    No Known Activations