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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. 4-RES-JB
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    Explanations

    references to scoring goals or activities related to scoring goals in sports

    oai_token-act-pair · gpt-3.5-turbo

    references to scoring goals in sports

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

    No Comments

    Negative Logits
     sclerosis
    -0.86
    enegger
    -0.83
    DragonMagazine
    -0.78
    Versions
    -0.75
     discounts
    -0.68
     layers
    -0.68
    TeX
    -0.66
    urrencies
    -0.64
    cale
    -0.64
    FY
    -0.63
    POSITIVE LOGITS
     scorer
    1.03
    keepers
    0.90
     scored
    0.90
     kicker
    0.90
    stre
    0.88
    boards
    0.87
    goal
    0.81
    animous
    0.80
    posts
    0.79
     striker
    0.77
    Activations Density 0.021%

    No Known Activations