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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 4311
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    Explanations

    people working in service positions, such as attendants, clerks, waiters, and waitresses

    oai_token-act-pair · gpt-3.5-turbo

    references to service roles or occupations in various settings

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Flavoring
    -0.82
    çīĪ
    -0.71
    theless
    -0.68
     Marketable
    -0.68
    orsche
    -0.68
    ationally
    -0.68
    IJ
    -0.68
    itars
    -0.66
     Born
    -0.65
    bsp
    -0.63
    POSITIVE LOGITS
    esses
    1.10
     attendants
    1.03
     attendant
    0.94
    ess
    0.91
     supervisor
    0.83
     waitress
    0.83
     clerk
    0.83
     cafeteria
    0.82
     maid
    0.81
     boun
    0.78
    Activations Density 0.188%

    No Known Activations