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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. 5-RES-JB
    6. 220
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    Explanations

    numerical statistics related to sports performance

    oai_token-act-pair · gpt-3.5-turbo

    opening parentheses in statistical or score-related contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     antim
    -0.81
     wre
    -0.80
     lull
    -0.73
     fres
    -0.72
     hiding
    -0.70
     artisan
    -0.70
     tremend
    -0.69
     antiv
    -0.68
     terr
    -0.68
    osate
    -0.68
    POSITIVE LOGITS
    including
    1.17
    excluding
    1.17
    which
    1.16
    formerly
    1.15
    although
    1.11
    both
    1.11
    also
    1.11
    via
    1.10
    pictured
    1.08
    mostly
    1.08
    Activations Density 0.107%

    No Known Activations