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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
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    Explanations

    references to meals or eating

    oai_token-act-pair · gpt-3.5-turbo

    references to meals or food-related concepts

    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
    orate
    -0.69
    ignty
    -0.68
    vernment
    -0.67
    idency
    -0.67
    inates
    -0.66
    aft
    -0.65
    rity
    -0.65
    hips
    -0.60
     Agency
    -0.60
     Negative
    -0.59
    POSITIVE LOGITS
     meal
    1.29
    worms
    1.20
     meals
    1.17
     Meal
    1.12
    worm
    0.94
     eaten
    0.89
     eater
    0.83
    eteria
    0.82
     buffet
    0.82
     breakfast
    0.82
    Activations Density 0.009%

    No Known Activations