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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. 1688
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    Explanations

    references to the city of Toronto

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "Toronto" and its associated sports teams

    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
    hardt
    -0.80
    ulative
    -0.74
    gins
    -0.73
    omez
    -0.73
     disse
    -0.72
    ultan
    -0.72
    ãĤ©
    -0.71
    ktop
    -0.69
    bler
    -0.69
    enegger
    -0.69
    POSITIVE LOGITS
     Maple
    1.07
     Argon
    1.07
     Raptors
    1.00
     Harbour
    0.99
     FC
    0.96
     Centre
    0.87
     Hydro
    0.86
     Heights
    0.77
     harbour
    0.76
     Mississ
    0.73
    Activations Density 0.042%

    No Known Activations