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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. 9-RES-JB
    6. 6335
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    INDEX
    Explanations

    mentions of food and dietary habits, specifically focusing on whole foods

    oai_token-act-pair · gpt-3.5-turbo

    terms related to whole foods and health

    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
    anwhile
    -0.69
    cing
    -0.64
    CU
    -0.63
    ANS
    -0.62
     Predators
    -0.62
    abilities
    -0.58
    IDS
    -0.58
    onson
    -0.58
    KER
    -0.57
    Fight
    -0.57
    POSITIVE LOGITS
    heartedly
    1.71
    hearted
    1.41
    meal
    1.09
     genome
    0.79
     hog
    0.77
     Foods
    0.72
     gam
    0.70
     wheat
    0.70
     genomes
    0.68
    orse
    0.67
    Activations Density 0.030%

    No Known Activations