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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. 4-RES-JB
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    Explanations

    mentions related to sports officiating and referees

    oai_token-act-pair · gpt-3.5-turbo

    terms related to officiating, penalties, and errors in sports

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

    No Comments

    Negative Logits
    Progress
    -1.02
    ILA
    -1.01
    opian
    -0.91
    Eva
    -0.80
    INTON
    -0.80
    quart
    -0.78
    Anonymous
    -0.78
    ĺħ
    -0.77
    bara
    -0.77
    negie
    -0.76
    POSITIVE LOGITS
     announ
    1.17
     referees
    1.09
     replay
    1.08
     announcer
    1.08
     jerseys
    1.06
     foul
    1.03
     SPORTS
    1.02
     penalty
    1.02
     scoreboard
    1.02
     referee
    0.99
    Activations Density 0.239%

    No Known Activations