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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. 3-RES-JB
    11. 16368
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    Explanations

    phrases related to sports, particularly describing player statistics and game outcomes

    oai_token-act-pair · gpt-3.5-turbo

    the preposition "with" indicating associations or relationships in the context of sports events

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    mart
    -0.71
    ati
    -0.70
    ajor
    -0.69
    omsky
    -0.67
    atically
    -0.66
    atos
    -0.65
    fort
    -0.65
    iltr
    -0.64
    chuk
    -0.64
    handler
    -0.64
    POSITIVE LOGITS
     regards
    1.37
     regard
    1.32
    stood
    1.31
     impunity
    1.15
    standing
    1.12
    draw
    1.03
    drawn
    1.03
     respect
    0.97
    holding
    0.96
     dignity
    0.79
    Activations Density 0.301%

    No Known Activations