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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. 5661
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    Explanations

    mentions of lunch

    oai_token-act-pair · gpt-3.5-turbo

    references to lunch

    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
    Constructed
    -0.73
    ignty
    -0.73
    oral
    -0.71
    mental
    -0.70
     extrap
    -0.69
    vernment
    -0.69
    Downloadha
    -0.67
    unknown
    -0.65
     Gemini
    -0.65
     Fundamental
    -0.65
    POSITIVE LOGITS
     lunch
    1.01
    eteria
    1.00
    bag
    0.95
     Lunch
    0.94
     meal
    0.88
     meals
    0.87
    wich
    0.87
    time
    0.86
    aturday
    0.84
     breakfast
    0.81
    Activations Density 0.009%

    No Known Activations