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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. 6-RES-JB
    11. 5516
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    Explanations

    phrases related to efficiency

    oai_token-act-pair · gpt-3.5-turbo

    references to efficiency and optimization

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    enegger
    -0.92
    FACE
    -0.72
    jong
    -0.72
    ortium
    -0.71
    acular
    -0.70
    Dream
    -0.68
    kers
    -0.68
     Sour
    -0.67
    clips
    -0.66
    warts
    -0.66
    POSITIVE LOGITS
     efficiency
    1.13
    iencies
    1.08
     efficient
    1.00
     inefficient
    0.99
     allocation
    0.91
     effic
    0.86
     tract
    0.81
    idious
    0.79
     optimization
    0.79
     alloc
    0.79
    Activations Density 0.025%

    No Known Activations