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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. 4-RES-JB
    6. 8182
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    Explanations

    specific percentage numbers in texts

    oai_token-act-pair · gpt-3.5-turbo

    quantitative data in percentages

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

    No Comments

    Negative Logits
    HCR
    -0.78
    ãĤ¡
    -0.77
    ĸļ
    -0.76
     Cassidy
    -0.76
     AVG
    -0.75
    ãĥ£
    -0.71
    ãĤ¯
    -0.70
     Osw
    -0.69
    ãĥ¼ãĥĨãĤ£
    -0.69
    earch
    -0.69
    POSITIVE LOGITS
    sized
    1.13
    legged
    1.06
    eight
    1.05
    tailed
    1.04
    year
    0.99
    percent
    0.98
    six
    0.96
    nine
    0.95
    hour
    0.93
    seven
    0.92
    Activations Density 0.054%

    No Known Activations