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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. 18011
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    Explanations

    references to daily activities or routines

    oai_token-act-pair · gpt-3.5-turbo

    contexts and references related to daily activities or routines

    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
    essee
    -0.80
    dinand
    -0.80
    OHN
    -0.79
    ename
    -0.76
    yrights
    -0.76
    xon
    -0.74
    artisan
    -0.74
    aye
    -0.73
    enic
    -0.72
    erala
    -0.71
    POSITIVE LOGITS
    motion
    1.15
     occurrence
    1.04
     routines
    0.99
     occurrences
    0.98
     routine
    0.96
     grind
    0.91
     necessities
    0.90
     commute
    0.88
     dose
    0.83
     reminders
    0.83
    Activations Density 0.042%

    No Known Activations