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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. 22636
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    Explanations

    words related to financial matters, particularly in the context of budgeting and spending

    oai_token-act-pair · gpt-3.5-turbo

    terms related to financial appropriations and funding

    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
    Oracle
    -0.88
    uber
    -0.83
    icle
    -0.80
    iquette
    -0.73
    ARDS
    -0.73
    âĢ¢âĢ¢âĢ¢âĢ¢
    -0.72
    âĸ¬
    -0.72
    hart
    -0.68
    ker
    -0.67
    Bre
    -0.67
    POSITIVE LOGITS
     appropriations
    1.28
     Appropriations
    1.15
    itures
    1.10
     appropriation
    1.05
     subcommittee
    1.03
     appropriated
    0.98
     committees
    0.91
     allocations
    0.85
     Appropri
    0.84
     authorization
    0.83
    Activations Density 0.018%

    No Known Activations