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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    7. Residual Stream
    9. 0-RES-JB
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    Explanations

    references to a sports team called "Warriors"

    oai_token-act-pair · gpt-3.5-turbo

    mentions of the "Warriors" as a sports team

    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
    anz
    -0.68
     populated
    -0.68
     Instrument
    -0.68
    rent
    -0.67
     matt
    -0.66
     instrument
    -0.64
    enna
    -0.63
     lending
    -0.62
    uggest
    -0.62
     depress
    -0.62
    POSITIVE LOGITS
     Warriors
    4.11
     Warrior
    2.07
    riors
    1.82
     Cavaliers
    1.81
     Blazers
    1.73
     warriors
    1.67
     Cavs
    1.60
     Pelicans
    1.59
     Sharks
    1.55
     Spartans
    1.53
    Activations Density 0.013%

    No Known Activations