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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. 9-RES-JB
    6. 780
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    INDEX
    Explanations

    sports-related terms and activities

    oai_token-act-pair · gpt-3.5-turbo

    mentions of various sports and athletic activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ptoms
    -0.92
     inspectors
    -0.77
    uid
    -0.74
     Amount
    -0.72
     Symptoms
    -0.72
     Ingredients
    -0.71
    isible
    -0.70
    selves
    -0.69
     constituents
    -0.69
     Notification
    -0.69
    POSITIVE LOGITS
     basketball
    1.27
     rugby
    1.25
     tennis
    1.16
     baseball
    1.15
     MMA
    1.14
    basketball
    1.14
     chess
    1.14
     cricket
    1.12
     boxing
    1.11
     volleyball
    1.10
    Activations Density 0.341%

    No Known Activations