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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. 0-RES-JB
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    Explanations

    mentions of meals or food items

    oai_token-act-pair · gpt-3.5-turbo

    references to meals

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ãĤ´
    -0.76
    bors
    -0.73
     Quinn
    -0.70
    tc
    -0.69
    ports
    -0.64
    projects
    -0.63
    der
    -0.63
    RC
    -0.61
     Prototype
    -0.61
    Ax
    -0.61
    POSITIVE LOGITS
     meal
    3.78
     Meal
    2.82
     meals
    2.73
    meal
    1.91
     dinner
    1.90
     supper
    1.85
     lunch
    1.85
     breakfast
    1.79
     dinners
    1.76
     snack
    1.72
    Activations Density 0.012%

    No Known Activations