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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 10-RES-JB
    6. 7483
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    Explanations

    sporting events and outcomes

    oai_token-act-pair · gpt-3.5-turbo

    mentions of losses in sports events

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    pmwiki
    -0.88
    erred
    -0.79
    aund
    -0.79
    natureconservancy
    -0.76
    DragonMagazine
    -0.75
    oola
    -0.75
    obbies
    -0.72
    tracks
    -0.71
    ersive
    -0.71
    Mods
    -0.70
    POSITIVE LOGITS
     Kansas
    1.08
     lowly
    1.07
     Pittsburgh
    1.06
     Detroit
    1.04
     Minnesota
    1.03
     Seattle
    1.01
     Houston
    1.00
     Oklahoma
    1.00
     Cincinnati
    0.99
     Carolina
    0.99
    Activations Density 0.075%

    No Known Activations