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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. 0-RES-JB
    11. 6753
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    INDEX
    Explanations

    mentions of drills and training exercises

    oai_token-act-pair · gpt-3.5-turbo

    references to drills or training exercises

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    Publisher
    -0.76
     publisher
    -0.74
     Lib
    -0.72
    iety
    -0.68
     Publishers
    -0.67
     Equality
    -0.65
     appealing
    -0.65
     ());
    -0.64
     Ending
    -0.64
     Chandra
    -0.64
    POSITIVE LOGITS
     drills
    3.92
     drill
    2.72
     Drill
    2.22
     drilled
    1.62
     drilling
    1.54
     exercises
    1.30
     workouts
    1.22
     scrim
    1.16
     formations
    1.13
     maneuvers
    1.12
    Activations Density 0.015%

    No Known Activations