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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. 4650
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    Explanations

    numbers related to sports statistics

    oai_token-act-pair · gpt-3.5-turbo

    numeric values associated with sports statistics and player counts

    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
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    No Comments

    Negative Logits
    6000
    -0.71
    atra
    -0.65
    agate
    -0.64
    Tube
    -0.64
    schild
    -0.64
    actionDate
    -0.64
    igmat
    -0.63
    atography
    -0.62
    gru
    -0.62
    biz
    -0.61
    POSITIVE LOGITS
     rookies
    1.33
     players
    1.24
     starters
    1.23
     quarterbacks
    1.20
     teams
    1.13
     seasons
    1.08
     rookie
    1.07
     playoff
    1.06
     preseason
    1.06
     finalists
    1.04
    Activations Density 0.183%

    No Known Activations