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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. 2-RES-JB
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    Explanations

    phrases related to different types of prevention measures and programs

    oai_token-act-pair · gpt-3.5-turbo

    concepts related to prevention strategies and measures in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    edes
    -0.85
    ells
    -0.76
    ebus
    -0.73
    erry
    -0.68
    enegger
    -0.68
    yss
    -0.68
    MX
    -0.67
    mpeg
    -0.67
    INGS
    -0.67
    eton
    -0.66
    POSITIVE LOGITS
     prevention
    1.07
     Prevention
    0.82
     screening
    0.79
     proble
    0.77
     screenings
    0.77
     allev
    0.76
     detection
    0.75
     preventive
    0.74
     awareness
    0.71
     cessation
    0.71
    Activations Density 0.013%

    No Known Activations