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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. 4-RES-JB
    11. 16643
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    Explanations

    words related to rules and regulations, particularly those with negative connotations

    oai_token-act-pair · gpt-3.5-turbo

    words related to legal or regulatory contexts

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

    No Comments

    Negative Logits
     Kiss
    -0.70
    ATCH
    -0.68
    Story
    -0.65
     Union
    -0.64
     Royale
    -0.62
     Aux
    -0.61
    ãĥ¯ãĥ³
    -0.61
    LLOW
    -0.59
     Variety
    -0.59
     sight
    -0.59
    POSITIVE LOGITS
    ifice
    1.17
    ict
    1.12
    gew
    1.11
    icts
    1.05
    uce
    1.05
    monton
    1.02
    ging
    1.01
    dy
    1.01
    nesday
    1.01
    irect
    0.99
    Activations Density 0.009%

    No Known Activations