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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. 9-RES-JB
    11. 23342
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    Explanations

    significant drops in various metrics or statistics

    oai_token-act-pair · gpt-3.5-turbo

    words related to declines and decreases in various metrics or statistics

    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
    alez
    -0.62
    Nev
    -0.62
    fill
    -0.62
     appl
    -0.61
     Founding
    -0.58
     sar
    -0.57
     pardon
    -0.56
    tein
    -0.56
     Success
    -0.56
     vo
    -0.56
    POSITIVE LOGITS
     sharply
    1.11
     drastically
    1.11
     markedly
    1.03
    graded
    1.02
     dramatically
    1.02
     considerably
    1.00
     substantially
    0.94
     marginally
    0.94
     significantly
    0.91
     precip
    0.91
    Activations Density 0.110%

    No Known Activations