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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. 11-RES-JB
    11. 23700
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    Explanations

    mentions of specific timeframes and events, particularly related to injuries or missed opportunities

    oai_token-act-pair · gpt-3.5-turbo

    references to seasons and injuries in sports contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    pires
    -0.66
    eson
    -0.62
     toget
    -0.59
    ieth
    -0.58
     indo
    -0.57
     differentiated
    -0.57
     likeness
    -0.56
     pedigree
    -0.56
    cellent
    -0.56
    ibles
    -0.55
    POSITIVE LOGITS
     due
    1.60
     owing
    1.44
    due
    1.32
     because
    1.20
    because
    1.08
     fearing
    1.03
     Unable
    1.01
    ecause
    1.00
    Due
    0.95
     Due
    0.94
    Activations Density 0.288%

    No Known Activations