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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. 9-RES-JB
    11. 18414
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    Explanations

    descriptions related to player performance and attributes in sports, particularly football

    oai_token-act-pair · gpt-3.5-turbo

    references to player evaluations and performance in sports

    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
    encies
    -0.77
    bara
    -0.75
     Ibid
    -0.75
    conom
    -0.74
    uits
    -0.72
    laws
    -0.72
    codes
    -0.72
    obia
    -0.69
    esthesia
    -0.69
    etry
    -0.68
    POSITIVE LOGITS
     rookie
    1.30
     starter
    1.20
     scorer
    1.19
     player
    1.18
     Rookie
    1.13
     sleeper
    1.10
     superstar
    1.08
     contender
    1.06
     passer
    1.06
     hitter
    1.06
    Activations Density 0.246%

    No Known Activations