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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 10-RES-JB
    11. 4736
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    Explanations

    quantitative information such as numbers and percentages

    oai_token-act-pair · gpt-3.5-turbo

    references to quantitative data and statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    uesday
    -0.68
    terday
    -0.60
    ovember
    -0.59
     yesterday
    -0.57
    henko
    -0.57
     winters
    -0.56
    celona
    -0.55
     fortnight
    -0.54
     summers
    -0.52
    stanbul
    -0.52
    POSITIVE LOGITS
    %.
    0.62
    .(
    0.61
    .*
    0.58
    .:
    0.57
    .<
    0.57
    `.
    0.56
    ="/
    0.56
    .</
    0.56
    ({
    0.55
    .]
    0.55
    Activations Density 0.847%

    No Known Activations