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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. 0-RES-JB
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    Explanations

    references to the sports team "Cardinals"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of sports teams and locations associated with them

    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
    sha
    -0.69
     Tek
    -0.66
     Sok
    -0.63
    shock
    -0.63
     fue
    -0.62
    RAW
    -0.61
    IFT
    -0.60
    UTF
    -0.60
    aida
    -0.60
     fibre
    -0.59
    POSITIVE LOGITS
     Cardinals
    3.85
     Cardinal
    1.84
     Cards
    1.83
     Cubs
    1.67
     Bengals
    1.65
     Rams
    1.62
     Louisville
    1.60
     Dodgers
    1.59
     Falcons
    1.56
     Braves
    1.55
    Activations Density 0.023%

    No Known Activations