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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. 4-RES-JB
    11. 12010
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    Explanations

    mentions of fitness-related activities or concepts

    oai_token-act-pair · gpt-3.5-turbo

    terms related to fitness and physical health

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

    No Comments

    Negative Logits
    akedown
    -0.76
    ectar
    -0.73
    âĸ¬
    -0.70
     Rockefeller
    -0.70
     hemorrh
    -0.68
    ãĥĥãĥī
    -0.68
     Overt
    -0.66
     gou
    -0.62
     Helpful
    -0.62
    neys
    -0.61
    POSITIVE LOGITS
     fitness
    1.05
     Trainer
    0.91
     regimen
    0.85
     trainer
    0.84
     credentials
    0.83
     Fitness
    0.81
    ability
    0.77
     endors
    0.77
     promot
    0.77
     trainers
    0.77
    Activations Density 0.013%

    No Known Activations