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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. 1-RES-JB
    11. 888
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    Explanations

    phrases related to ice hockey and players involved in the game

    oai_token-act-pair · gpt-3.5-turbo

    mentions of hockey teams and defenseman in the text

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Eps
    -0.77
    Mega
    -0.73
     IPM
    -0.67
    agy
    -0.66
    EngineDebug
    -0.66
     Kin
    -0.65
     Blackwell
    -0.63
    Bird
    -0.63
     Doe
    -0.63
    Bee
    -0.63
    POSITIVE LOGITS
    ipeg
    1.13
     Sabres
    1.08
     defenseman
    1.04
     rink
    1.02
     goaltender
    1.02
     hockey
    0.98
     puck
    0.96
     Oilers
    0.95
     Canadiens
    0.92
     Blackhawks
    0.91
    Activations Density 0.055%

    No Known Activations