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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. 10-RES-JB
    11. 16467
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    Explanations

    mentions of long-term negative consequences on health and well-being

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating negative consequences or risks to health and safety

    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
     largeDownload
    -0.67
    illon
    -0.67
    urai
    -0.65
    htaking
    -0.64
    ropolitan
    -0.60
    OB
    -0.60
    erd
    -0.60
    gor
    -0.58
    rine
    -0.57
     Parables
    -0.56
    POSITIVE LOGITS
     subsequent
    1.30
     future
    1.18
     downstream
    1.13
     later
    1.11
     eventual
    1.01
     consequ
    1.00
     unsuspecting
    1.00
     otherwise
    0.95
     thereafter
    0.94
     ensuing
    0.94
    Activations Density 0.495%

    No Known Activations