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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
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    7. Residual Stream
    9. 4-RES-JB
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    Explanations

    references to passing in a sports context, particularly focused on football

    oai_token-act-pair · gpt-3.5-turbo

    references to passing plays in sports, particularly football

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

    No Comments

    Negative Logits
    obook
    -0.71
    aples
    -0.66
    ifully
    -0.64
     GOODMAN
    -0.63
    auga
    -0.62
     Sadd
    -0.62
     plur
    -0.62
     Ink
    -0.62
     region
    -0.61
    antha
    -0.61
    POSITIVE LOGITS
    wd
    0.98
     Passing
    0.84
    phrase
    0.78
    aways
    0.76
    yards
    0.75
     rusher
    0.75
     muster
    0.75
    away
    0.73
    ives
    0.73
    smanship
    0.71
    Activations Density 0.010%

    No Known Activations