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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. 9-RES-JB
    11. 19383
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    Explanations

    phrases related to violent events and tragedies

    oai_token-act-pair · gpt-3.5-turbo

    references to mass shootings and the related aftermath or context

    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
    dit
    -1.01
    DIR
    -0.80
     carrot
    -0.78
    utical
    -0.75
     chores
    -0.74
     IPM
    -0.74
    ERC
    -0.70
     carrots
    -0.69
    Medium
    -0.69
    Publisher
    -0.68
    POSITIVE LOGITS
     gunman
    1.24
     shootings
    1.15
     Pulse
    1.09
     assailant
    1.08
     massacre
    1.07
    anooga
    1.05
     Charlottesville
    1.05
     shooter
    1.04
     rampage
    1.02
     Haram
    1.01
    Activations Density 0.570%

    No Known Activations