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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. 6-RES-JB
    6. 1444
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    Explanations

    mentions of sharp objects or blades, potentially related to weaponry

    oai_token-act-pair · gpt-3.5-turbo

    references to blades, particularly in various contexts, including knives and tools

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    quickShipAvailable
    -0.89
    ADRA
    -0.80
    gdala
    -0.80
    bos
    -0.79
     Niet
    -0.76
    ESA
    -0.71
    ravel
    -0.70
    riad
    -0.70
    phis
    -0.68
    EMBER
    -0.67
    POSITIVE LOGITS
     blades
    1.12
    tips
    1.03
     Runner
    0.98
     blade
    0.97
    tip
    0.90
    blade
    0.89
    Blade
    0.83
     Cutter
    0.82
     knives
    0.80
    hawk
    0.80
    Activations Density 0.019%

    No Known Activations