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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. 10-RES-JB
    11. 6203
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    Explanations

    sports statistics

    oai_token-act-pair · gpt-3.5-turbo

    statistics related to athletic performance and achievements

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Processing
    -0.65
     ABE
    -0.64
    bys
    -0.63
    Asia
    -0.61
    cul
    -0.61
     Gum
    -0.57
    wikipedia
    -0.57
    abus
    -0.57
     Contents
    -0.56
     Gors
    -0.55
    POSITIVE LOGITS
     averaging
    0.90
     offensively
    0.89
     throughout
    0.82
     compared
    0.82
     overall
    0.79
     athlet
    0.78
     against
    0.77
     while
    0.77
     averaged
    0.76
     during
    0.76
    Activations Density 0.162%

    No Known Activations