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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. 11-RES-JB
    6. 10516
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    INDEX
    Explanations

    historical or insightful lessons gleaned from various contexts

    oai_token-act-pair · gpt-3.5-turbo

    references to lessons and learning experiences

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    omin
    -0.72
    yy
    -0.72
    trak
    -0.67
    urat
    -0.63
    uve
    -0.63
    ãĥ¢
    -0.63
    gur
    -0.63
     occupancy
    -0.62
    yip
    -0.61
    ãĥı
    -0.60
    POSITIVE LOGITS
     Learned
    1.67
     learned
    1.62
     learnt
    1.55
     lesson
    1.26
     lessons
    1.22
    Lear
    1.12
    learn
    1.12
     taught
    1.08
     glean
    1.01
     Lessons
    0.93
    Activations Density 0.078%

    No Known Activations