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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. 9-RES-JB
    11. 2764
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    Explanations

    phrases related to rules or instructions being applied in various contexts

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to rules and regulations

    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
    adish
    -0.68
    cious
    -0.62
    asus
    -0.61
     Seymour
    -0.59
     Hercules
    -0.59
    apter
    -0.59
    berries
    -0.58
    ilde
    -0.57
     Gow
    -0.56
    cknowled
    -0.55
    POSITIVE LOGITS
     equally
    0.90
     exclusively
    0.81
     uniformly
    0.81
     universally
    0.80
     apply
    0.80
     irrespective
    0.78
     regardless
    0.76
     everywhere
    0.76
     unto
    0.75
     applies
    0.73
    Activations Density 0.056%

    No Known Activations