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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 7-RES-JB
    6. 4274
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    Explanations

    instances of mentions or discussions of the use of force, particularly in law enforcement contexts

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to the use of force, particularly in law enforcement and military contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Rib
    -0.73
     Lime
    -0.69
     Coil
    -0.66
    akis
    -0.63
    unct
    -0.63
    ixture
    -0.63
    uez
    -0.61
     Lov
    -0.61
     Adin
    -0.61
    seq
    -0.61
    POSITIVE LOGITS
     inappropriately
    0.98
     sparing
    0.96
     responsibly
    0.95
     wisely
    0.95
     efficiently
    0.93
     GOODMAN
    0.92
     unlawfully
    0.91
     offensively
    0.85
     defensively
    0.83
     indiscrim
    0.81
    Activations Density 0.162%

    No Known Activations