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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 7-RES-JB
    6. 653
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    Explanations

    phrases related to potential and performance evaluation in a sports context, including words related to player skills and impact on the team

    oai_token-act-pair · gpt-3.5-turbo

    expressions of potential and future success

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    respond
    -0.70
    yrics
    -0.69
    rote
    -0.65
     humour
    -0.64
     Capitalism
    -0.62
     censorship
    -0.62
     Carnival
    -0.62
     Shank
    -0.61
     Advertising
    -0.61
     censored
    -0.61
    POSITIVE LOGITS
     someday
    1.29
     anytime
    1.00
     Rookie
    0.99
     rookie
    0.98
    omever
    0.98
     breakout
    0.97
     matchup
    0.93
     underrated
    0.91
     offensively
    0.86
     offseason
    0.85
    Activations Density 0.649%

    No Known Activations