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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
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    text related to sports matches and victories

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to sports matches and their outcomes

    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
    pmwiki
    -0.98
    erred
    -0.85
     Journals
    -0.82
    iscal
    -0.77
    milo
    -0.73
    aund
    -0.72
    DragonMagazine
    -0.71
    attribute
    -0.70
    idav
    -0.70
     curric
    -0.70
    POSITIVE LOGITS
     lowly
    1.10
     Kansas
    1.04
     Pittsburgh
    1.03
     Notre
    1.01
     Tampa
    1.00
     Dallas
    0.98
     Toledo
    0.98
     Carolina
    0.97
     Ole
    0.97
     Detroit
    0.97
    Activations Density 0.089%

    No Known Activations