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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. 8-RES-JB
    11. 756
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    Explanations

    words related to values, technology, finances, and historical backgrounds

    oai_token-act-pair · gpt-3.5-turbo

    concepts related to values and entrepreneurship

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 8-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.8.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.8.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    8
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    dyl
    -0.59
     gren
    -0.55
    ,[
    -0.54
     whoever
    -0.54
    ayn
    -0.52
     [*
    -0.52
    )."
    -0.51
     muster
    -0.51
     tv
    -0.50
     thereto
    -0.50
    POSITIVE LOGITS
     Approach
    0.98
     References
    0.90
     Costs
    0.88
     Challenges
    0.87
     Comparison
    0.85
     Perspective
    0.85
     Versus
    0.84
     Differences
    0.84
     Overview
    0.84
     Conclusion
    0.83
    Activations Density 0.847%

    No Known Activations