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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. 4-RES-JB
    11. 7813
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    Explanations

    ingredients related to cooking with an emphasis on freshness

    oai_token-act-pair · gpt-3.5-turbo

    references to fresh food and ingredients

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

    No Comments

    Negative Logits
    xual
    -0.84
    ĸļ
    -0.84
    orem
    -0.82
    peak
    -0.76
     DRAG
    -0.75
    berra
    -0.73
     seism
    -0.71
     guiActiveUn
    -0.71
    IRC
    -0.69
    chairs
    -0.68
    POSITIVE LOGITS
     vegetables
    1.00
     vegetable
    0.93
     oats
    0.91
     veggies
    0.91
     foods
    0.90
     herbs
    0.88
     strawberries
    0.83
    rafted
    0.82
     ingredients
    0.81
     cured
    0.81
    Activations Density 0.092%

    No Known Activations