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    1. Home
    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. 7580
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    Explanations

    references to heavily armed police units like SWAT teams

    oai_token-act-pair · gpt-3.5-turbo

    terms related to SWAT teams and military presence in law enforcement

    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
    criptions
    -0.80
    Rate
    -0.75
     DRAG
    -0.75
    ranged
    -0.71
    ð
    -0.71
    yt
    -0.69
    hare
    -0.69
    eas
    -0.67
    iard
    -0.66
    lected
    -0.66
    POSITIVE LOGITS
    ilitary
    0.92
     militar
    0.87
     standoff
    0.85
     SWAT
    0.80
    ormal
    0.79
    intendent
    0.79
     LAPD
    0.76
     SEAL
    0.75
     Ops
    0.72
     Officers
    0.71
    Activations Density 0.082%

    No Known Activations