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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. 7-RES-JB
    6. 17579
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    Explanations

    references to schedules

    oai_token-act-pair · gpt-3.5-turbo

    references to schedules and routines

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    vironment
    -0.76
    geoning
    -0.75
    inals
    -0.72
    tein
    -0.71
    tymology
    -0.71
    oks
    -0.69
    ston
    -0.68
    oji
    -0.68
    iants
    -0.68
    ternity
    -0.67
    POSITIVE LOGITS
     schedules
    1.09
    dule
    0.98
     schedule
    0.94
     Sched
    0.80
     scheduling
    0.79
     assignments
    0.76
     TBD
    0.76
     sched
    0.75
     calendars
    0.73
     appointments
    0.73
    Activations Density 0.029%

    No Known Activations