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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. 4-RES-JB
    6. 23900
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    Explanations

    phrases related to large quantities or numbers

    oai_token-act-pair · gpt-3.5-turbo

    references to large quantities or amounts

    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
     Seat
    -0.76
     Commissioners
    -0.76
    Redditor
    -0.75
    Exit
    -0.73
    âĸ¬
    -0.70
    Blade
    -0.69
    Delivery
    -0.69
     Tycoon
    -0.65
     Rebellion
    -0.65
    Commission
    -0.65
    POSITIVE LOGITS
    poons
    1.10
    cale
    1.10
    ensical
    1.03
     amounts
    1.01
    omething
    1.01
     quantities
    0.98
    pace
    0.98
    paces
    0.97
    ngth
    0.97
    ugar
    0.97
    Activations Density 0.041%

    No Known Activations