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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. 3-RES-JB
    11. 9447
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    Explanations

    mentions of the number of hours spent on various activities

    oai_token-act-pair · gpt-3.5-turbo

    references to the number of hours worked or spent on various activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    LECT
    -0.81
    esan
    -0.75
    Cole
    -0.74
    chance
    -0.72
    Shock
    -0.69
     Culture
    -0.68
    geist
    -0.67
    dinand
    -0.66
    isol
    -0.66
    Sov
    -0.66
    POSITIVE LOGITS
    glass
    1.01
    mith
    0.99
     Ago
    0.97
     ILCS
    0.95
    hops
    0.93
    poons
    0.86
    endment
    0.85
     hrs
    0.84
     elapsed
    0.83
    pring
    0.83
    Activations Density 0.030%

    No Known Activations