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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. 15437
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    Explanations

    shots taken in soccer matches from various positions on the field

    oai_token-act-pair · gpt-3.5-turbo

    references to locations and areas related to sports fields or goals

    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
    conom
    -0.76
    ItemImage
    -0.74
     Canaver
    -0.68
     Pricing
    -0.67
    ibur
    -0.66
    netflix
    -0.63
    OUP
    -0.62
    FactoryReloaded
    -0.61
    bol
    -0.61
    ItemThumbnailImage
    -0.60
    POSITIVE LOGITS
     midfield
    1.07
     basket
    1.02
     goal
    1.00
     rim
    0.98
     center
    0.97
     backfield
    0.96
     outfield
    0.93
     scoreboard
    0.89
     centre
    0.89
     middle
    0.85
    Activations Density 0.105%

    No Known Activations