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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. 5-RES-JB
    6. 11219
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    Explanations

    words related to work shifts and responsibilities

    oai_token-act-pair · gpt-3.5-turbo

    references to work shifts or schedules

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    gom
    -0.84
     Seym
    -0.84
    Interstitial
    -0.80
    gdala
    -0.74
    gil
    -0.69
    amina
    -0.68
    NetMessage
    -0.68
    çĦ
    -0.65
    MJ
    -0.64
    chu
    -0.63
    POSITIVE LOGITS
     shift
    0.99
     shifts
    0.89
    shift
    0.87
    overs
    0.81
    over
    0.81
     Shift
    0.80
    iple
    0.79
     shifting
    0.77
     gears
    0.77
    arity
    0.74
    Activations Density 0.018%

    No Known Activations