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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. 9-RES-JB
    11. 1042
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    Explanations

    specific mentions of drinking or drinking-related activities

    oai_token-act-pair · gpt-3.5-turbo

    references to drinking and beverages

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Sharif
    -0.84
    ural
    -0.71
     Parenthood
    -0.69
     notch
    -0.69
    theless
    -0.68
     Postal
    -0.65
    urally
    -0.64
    ality
    -0.64
    cephal
    -0.63
    iasis
    -0.60
    POSITIVE LOGITS
    cohol
    1.16
     bottles
    1.11
    water
    1.09
     beverages
    1.08
     drinkers
    1.07
     alcohol
    1.04
     beverage
    0.99
     Drink
    0.99
     drinking
    0.98
     brewed
    0.98
    Activations Density 0.053%

    No Known Activations