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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. 9-RES-JB
    6. 20563
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    Explanations

    words related to scoring, rewards, and progression in a competitive context

    oai_token-act-pair · gpt-3.5-turbo

    terms related to scoring or gaining points in games

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    OSP
    -0.69
    eatures
    -0.63
     unanim
    -0.63
    odynam
    -0.63
     Franch
    -0.62
     Babel
    -0.62
     enthusi
    -0.62
     bod
    -0.61
    inson
    -0.61
     skelet
    -0.60
    POSITIVE LOGITS
     Gained
    1.17
     expended
    1.16
     accumulated
    1.13
     accrued
    1.11
     deducted
    1.08
     gained
    1.07
     earned
    1.07
     awarded
    1.05
     allocated
    1.03
     allotted
    0.98
    Activations Density 0.278%

    No Known Activations