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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 15637
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    Explanations

    numeric information structured in a specific way, such as times, dates, scores, and statistics

    oai_token-act-pair · gpt-3.5-turbo

    specific numerical data related to sports events

    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
     vaping
    -0.82
     prolifer
    -0.81
     polymorph
    -0.80
    xual
    -0.79
     perfume
    -0.78
     augment
    -0.77
     behavi
    -0.76
     designer
    -0.76
     retard
    -0.75
     manifest
    -0.75
    POSITIVE LOGITS
    Players
    1.38
    Score
    1.38
    Winner
    1.30
    Tickets
    1.29
    Saturday
    1.29
    Sunday
    1.27
    Stats
    1.24
    Coach
    1.23
    Record
    1.23
    Wednesday
    1.21
    Activations Density 0.254%

    No Known Activations