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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. 3-RES-JB
    11. 8130
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    Explanations

    mentions of sports fans, particularly their enthusiasm and behavior

    oai_token-act-pair · gpt-3.5-turbo

    references to fans or audiences of sports

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    olon
    -0.65
     srfAttach
    -0.62
    nom
    -0.62
    abus
    -0.61
    EDIT
    -0.61
     Sett
    -0.60
    ONS
    -0.60
    ateral
    -0.60
     Solomon
    -0.60
     batch
    -0.59
    POSITIVE LOGITS
    atics
    0.97
    ubs
    0.95
     Fans
    0.94
     fans
    0.93
    haw
    0.92
     cheered
    0.90
    igans
    0.88
    atical
    0.88
    verson
    0.86
    Fans
    0.86
    Activations Density 0.023%

    No Known Activations