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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. 6559
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    Explanations

    references to field goals in sports

    oai_token-act-pair · gpt-3.5-turbo

    terms related to sports statistics and scoring

    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
     Seas
    -0.71
     Sparkle
    -0.71
     Carbuncle
    -0.70
     Helpful
    -0.67
     Hots
    -0.67
     Proud
    -0.65
     Cald
    -0.65
     Bubble
    -0.63
     Roof
    -0.63
    ynes
    -0.63
    POSITIVE LOGITS
    hand
    0.84
    writing
    0.77
    score
    0.77
    stop
    0.75
     appearances
    0.75
    goal
    0.75
    master
    0.74
    office
    0.72
    hog
    0.71
    force
    0.71
    Activations Density 0.146%

    No Known Activations