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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. 7-RES-JB
    11. 1532
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    Explanations

    terms related to prevention programs and measures, particularly in the context of specific issues such as crime, medical conditions, and accidents

    oai_token-act-pair · gpt-3.5-turbo

    concepts related to prevention programs and initiatives

    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
    pload
    -0.79
     monop
    -0.77
    asonic
    -0.75
    hest
    -0.74
    gling
    -0.72
    mpeg
    -0.70
    othe
    -0.70
    puted
    -0.69
    hetti
    -0.68
    umo
    -0.68
    POSITIVE LOGITS
     outreach
    1.12
     strategies
    1.01
     programs
    0.95
     programmes
    0.93
     Strategies
    0.89
     awareness
    0.88
     initiatives
    0.87
     Programs
    0.85
     prevention
    0.84
     policing
    0.83
    Activations Density 0.171%

    No Known Activations