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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. 6-RES-JB
    11. 17638
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    Explanations

    phrases related to time or preparation

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to planning or actions taken prior to an event

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Flavoring
    -0.76
    BuyableInstoreAndOnline
    -0.73
    DCS
    -0.72
    APTER
    -0.72
    ranch
    -0.68
    CHAPTER
    -0.67
    cu
    -0.66
    little
    -0.66
    ikes
    -0.65
    asca
    -0.65
    POSITIVE LOGITS
     screening
    0.89
     screenings
    0.88
    noon
    0.85
     scheduling
    0.81
     planning
    0.80
     booking
    0.72
     planner
    0.72
     staging
    0.70
     schedules
    0.69
     schedule
    0.68
    Activations Density 0.016%

    No Known Activations