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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. 4-RES-JB
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    Explanations

    terms related to productivity

    oai_token-act-pair · gpt-3.5-turbo

    concepts and discussions related to productivity in the workplace

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

    No Comments

    Negative Logits
    kef
    -0.65
    HEAD
    -0.65
    enegger
    -0.64
    Winged
    -0.63
    phan
    -0.63
     Dracula
    -0.62
    LECT
    -0.62
    oning
    -0.62
    cot
    -0.60
    joining
    -0.60
    POSITIVE LOGITS
     productivity
    0.95
    ivity
    0.88
    iencies
    0.85
     improvement
    0.79
     enhancement
    0.78
     efficiency
    0.76
     gains
    0.76
     quot
    0.74
    rious
    0.74
     enh
    0.73
    Activations Density 0.010%

    No Known Activations