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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
    11. 2687
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    Explanations

    references to large animals, particularly bears and other wildlife

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    animals typically associated with wilderness and danger

    oai_token-act-pair · gpt-3.5-turbo
    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
    pring
    -0.79
    mberg
    -0.77
    paces
    -0.76
    nyder
    -0.74
    uries
    -0.74
    ources
    -0.74
    ettings
    -0.73
    hip
    -0.72
    rity
    -0.72
    ometimes
    -0.71
    POSITIVE LOGITS
     carc
    1.04
     beetle
    1.02
    fish
    1.01
     hunter
    0.91
     corpse
    0.90
     crab
    0.82
    hawk
    0.80
    hunter
    0.80
     hump
    0.80
     turtle
    0.80
    Activations Density 0.136%

    No Known Activations