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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. 2655
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    Explanations

    phrases indicating a sense of loss or missed opportunity

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to missing opportunities or events

    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
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    No Comments

    Negative Logits
     rall
    -0.64
     fundament
    -0.63
    elf
    -0.59
    Bear
    -0.59
     confir
    -0.59
    oreal
    -0.59
    MR
    -0.58
    Zip
    -0.58
     attendant
    -0.58
    sit
    -0.57
    POSITIVE LOGITS
    paces
    1.03
     altogether
    0.85
    casts
    0.75
     opportunities
    0.70
     spectacular
    0.70
    groups
    0.69
     scholarships
    0.68
    ertodd
    0.68
     entirely
    0.67
     miser
    0.66
    Activations Density 0.055%

    No Known Activations