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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. 3-RES-JB
    11. 18627
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    Explanations

    mentions of fresh ingredients for food preparation

    oai_token-act-pair · gpt-3.5-turbo

    references to freshness in foods

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     guiActiveUn
    -0.85
    peak
    -0.78
     seism
    -0.76
    ĸļ
    -0.75
    berra
    -0.73
    isSpecialOrderable
    -0.70
    emonic
    -0.70
     enforce
    -0.69
    hler
    -0.68
     Vance
    -0.67
    POSITIVE LOGITS
     vegetables
    0.90
     harvested
    0.89
     oats
    0.81
     vegetable
    0.80
     grains
    0.80
     dehyd
    0.79
     ingredients
    0.79
     dried
    0.79
    houses
    0.79
     cured
    0.78
    Activations Density 0.083%

    No Known Activations