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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. 4-RES-JB
    11. 17040
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    Explanations

    mentions of the activity of 'practice' in various contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to sports practices

    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
    ailable
    -0.69
    sea
    -0.69
    THER
    -0.66
    proxy
    -0.64
    ebook
    -0.62
    prop
    -0.62
    vana
    -0.61
    ahime
    -0.60
    QL
    -0.59
    Auth
    -0.59
    POSITIVE LOGITS
     regimen
    0.93
     sessions
    0.90
    ctor
    0.88
     session
    0.85
     Grounds
    0.83
     Practices
    0.82
     practice
    0.82
     workouts
    0.80
     routines
    0.78
     Practice
    0.77
    Activations Density 0.022%

    No Known Activations