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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. 3-RES-JB
    11. 6252
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    Explanations

    words related to educational activities, specifically lectures

    oai_token-act-pair · gpt-3.5-turbo

    references to lectures

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    adjusted
    -0.70
    elly
    -0.67
    uilt
    -0.66
    balanced
    -0.63
    imposed
    -0.63
    mental
    -0.62
    printed
    -0.61
    dating
    -0.60
    bably
    -0.60
     preservation
    -0.60
    POSITIVE LOGITS
     Lect
    1.12
    ĸļ
    0.98
     lectures
    0.90
    ysis
    0.87
    gow
    0.86
    ¿½
    0.83
    inar
    0.81
     lecture
    0.80
     seminars
    0.78
    ures
    0.77
    Activations Density 0.009%

    No Known Activations