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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. 8-RES-JB
    11. 8965
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    Explanations

    phrases related to sports training and practice

    oai_token-act-pair · gpt-3.5-turbo

    terms related to training and practice activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    OGR
    -0.80
    obal
    -0.77
    pie
    -0.75
    ecause
    -0.70
    ropy
    -0.69
    eous
    -0.68
    ACP
    -0.68
    chu
    -0.67
    emonic
    -0.67
    osi
    -0.65
    POSITIVE LOGITS
     sessions
    1.06
     rosters
    0.99
     session
    0.98
     schedule
    0.96
     schedules
    0.95
     workouts
    0.93
     regimen
    0.92
     scrimmage
    0.88
     squad
    0.88
    aturday
    0.87
    Activations Density 0.091%

    No Known Activations