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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. 7-RES-JB
    11. 17869
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    Explanations

    phrases related to achieving goals or objectives

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "achieve" and related variations

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
    cloth
    -0.71
    gnu
    -0.70
    ©¶æ
    -0.70
    osate
    -0.66
     corro
    -0.64
    seed
    -0.64
    RNA
    -0.63
    dr
    -0.62
     chrom
    -0.61
    PLA
    -0.61
    POSITIVE LOGITS
     attainment
    0.92
     mastery
    0.87
     greatness
    0.86
     fruition
    0.86
     parity
    0.85
     achievement
    0.84
    ments
    0.83
     completion
    0.82
     accomplishment
    0.82
     immortality
    0.81
    Activations Density 0.044%

    No Known Activations