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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. 2689
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    Explanations

    references to beverages, particularly focusing on coffee, tea, wine, and water

    oai_token-act-pair · gpt-3.5-turbo

    references to beverages, particularly cups of coffee, tea, and wine

    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
    rencies
    -0.76
    urers
    -0.75
    hou
    -0.72
    heses
    -0.70
    indu
    -0.70
    isodes
    -0.70
    alties
    -0.70
    iblings
    -0.69
    yrs
    -0.69
    brates
    -0.68
    POSITIVE LOGITS
     soda
    0.94
     champagne
    0.92
     wine
    0.90
     coffee
    0.88
     tea
    0.85
     beer
    0.84
     soup
    0.84
     juice
    0.83
     vodka
    0.82
     whiskey
    0.81
    Activations Density 0.087%

    No Known Activations