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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. 6-RES-JB
    11. 13619
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    Explanations

    adjectives or descriptive terms related to opportunities, mainly focusing on chances to score or create offensive plays

    oai_token-act-pair · gpt-3.5-turbo

    references to scoring opportunities and possession in sports contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    enegger
    -0.82
    çĶ°
    -0.75
    coat
    -0.73
    Corp
    -0.70
    Beta
    -0.70
    Eth
    -0.68
    Reviewed
    -0.68
    Rated
    -0.67
    natureconservancy
    -0.67
    ONY
    -0.67
    POSITIVE LOGITS
     scorer
    0.99
     turnovers
    0.93
     bounce
    0.89
     midfield
    0.87
     batted
    0.85
     conceded
    0.83
     scoring
    0.83
     offensively
    0.81
     bounces
    0.80
     collisions
    0.79
    Activations Density 0.198%

    No Known Activations