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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    Explanations

    references to dragons and sharks

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "Dragons" and "Sharks."

    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
     sep
    -0.72
    occup
    -0.71
    immigrant
    -0.70
     infl
    -0.63
    ieg
    -0.63
     affecting
    -0.62
     mute
    -0.62
    riter
    -0.62
     utilization
    -0.62
     nut
    -0.61
    POSITIVE LOGITS
     Dragons
    4.12
     DRAG
    1.67
     dragons
    1.52
     Sharks
    1.48
     Demons
    1.40
    agons
    1.37
     Wolves
    1.33
     Titans
    1.29
     Lions
    1.26
     Wizards
    1.25
    Activations Density 0.016%

    No Known Activations