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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. 9262
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    INDEX
    Explanations

    references to wireless technology, specifically focusing on routers and networks

    oai_token-act-pair · gpt-3.5-turbo

    references to wireless technology and networking

    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
    gio
    -0.82
    auder
    -0.80
     Abram
    -0.80
    steen
    -0.80
    udo
    -0.79
    osa
    -0.79
    uations
    -0.79
    erva
    -0.78
    zanne
    -0.78
     Yard
    -0.77
    POSITIVE LOGITS
     connectivity
    1.10
     routers
    1.09
     router
    1.05
     hots
    1.01
     networking
    1.00
     wireless
    0.95
     networks
    0.93
     carriers
    0.93
     devices
    0.92
     headsets
    0.90
    Activations Density 0.034%

    No Known Activations