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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. 16696
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    Explanations

    occurrences related to sports defeats

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    references to sports outcomes, particularly wins and losses

    oai_token-act-pair · gpt-3.5-turbo
    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
     Journals
    -0.70
    ources
    -0.69
     journals
    -0.67
     popul
    -0.66
     curric
    -0.66
     reputable
    -0.66
     trademarks
    -0.65
     lawy
    -0.64
     intermedi
    -0.64
     certific
    -0.63
    POSITIVE LOGITS
     against
    0.95
    against
    0.90
     loss
    0.82
     defeat
    0.80
     halftime
    0.78
    wich
    0.77
     finale
    0.77
     shootout
    0.76
    sburgh
    0.76
    Seattle
    0.76
    Activations Density 0.215%

    No Known Activations