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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 1-RES-JB
    6. 14073
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    Explanations

    terms related to the brewing process or breweries

    oai_token-act-pair · gpt-3.5-turbo

    terms related to brewing and the brewing industry

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    olphins
    -0.82
    phis
    -0.81
    phia
    -0.79
    eah
    -0.77
    obo
    -0.74
     partName
    -0.73
     Hornets
    -0.71
    elo
    -0.70
     Grizzlies
    -0.70
    itars
    -0.70
    POSITIVE LOGITS
     brewing
    1.45
     brewed
    1.37
     brewer
    1.06
    Brew
    1.02
     ferment
    1.02
     brew
    1.00
     brewers
    0.99
     beer
    0.86
     fermentation
    0.82
     tea
    0.82
    Activations Density 0.007%

    No Known Activations