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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. 0-RES-JB
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    Explanations

    mentions of referees

    oai_token-act-pair · gpt-3.5-turbo

    references to referees and officiating in sports contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Heights
    -0.72
    atl
    -0.72
     Passage
    -0.71
    Mill
    -0.70
    acs
    -0.68
    umes
    -0.67
     Peak
    -0.67
    wx
    -0.67
     Hyde
    -0.65
    anche
    -0.63
    POSITIVE LOGITS
     referee
    4.00
     referees
    3.10
     offic
    2.06
    eree
    2.01
     moderator
    1.36
     announcer
    1.34
     spectator
    1.34
     refere
    1.30
     spectators
    1.27
     adjud
    1.24
    Activations Density 0.026%

    No Known Activations