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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. 396
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    INDEX
    Explanations

    instances of 'Q&A' or question and answer sessions

    oai_token-act-pair · gpt-3.5-turbo

    references to question and answer sessions

    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
    intent
    -0.80
    wikipedia
    -0.73
    fell
    -0.71
    sea
    -0.70
    bats
    -0.69
    acements
    -0.69
    origin
    -0.68
    EStreamFrame
    -0.68
     ãĤµãĥ¼ãĥĨãĤ£ãĥ¯ãĥ³
    -0.67
    sei
    -0.67
    POSITIVE LOGITS
     session
    1.27
     sessions
    1.19
     Session
    0.94
     interview
    0.80
     conversation
    0.78
     guru
    0.78
     moder
    0.78
    cation
    0.77
     Answers
    0.77
     panel
    0.76
    Activations Density 0.073%

    No Known Activations