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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. 10-RES-JB
    6. 9535
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    Explanations

    phrases related to risks, hazards, and potential harm

    oai_token-act-pair · gpt-3.5-turbo

    terms related to health risks and safety concerns

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    swick
    -0.76
    Blocks
    -0.71
    lio
    -0.68
    vez
    -0.67
    ggles
    -0.65
    gdala
    -0.63
    atters
    -0.62
    vil
    -0.62
    ership
    -0.62
    FTWARE
    -0.62
    POSITIVE LOGITS
     incurred
    1.20
     arising
    1.15
     associated
    1.12
     consequences
    1.08
     attributable
    1.06
     inherent
    1.04
     outweigh
    1.03
     outwe
    1.00
     resulting
    0.99
     stemming
    0.98
    Activations Density 0.271%

    No Known Activations