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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. 7-RES-JB
    11. 14258
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    Explanations

    phrases related to serving or presenting food

    oai_token-act-pair · gpt-3.5-turbo

    instructions related to food preparation and serving

    oai_token-act-pair · gpt-4o-mini
    Triggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Negative Logits
    sonian
    -0.75
    peria
    -0.72
    ilateral
    -0.72
    orph
    -0.72
     Chase
    -0.71
    usting
    -0.69
    ascus
    -0.68
    sis
    -0.67
    seed
    -0.65
     converter
    -0.65
    POSITIVE LOGITS
     meals
    1.00
     servings
    0.92
     drinks
    0.86
    maid
    0.85
     beverages
    0.79
     brunch
    0.79
     foods
    0.79
     snacks
    0.77
     Spoon
    0.77
     pancakes
    0.75
    Activations Density 0.048%

    No Known Activations