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    1. Home
    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. 716
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    INDEX
    Explanations

    assertions, claims, beliefs, understandings, reports, notes, and announcements made about specific events or situations

    oai_token-act-pair · gpt-3.5-turbo

    statements related to claims, beliefs, and expectations

    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
    ap
    -0.77
    avorite
    -0.77
    appings
    -0.70
    isode
    -0.68
    obos
    -0.68
    ROM
    -0.67
    ced
    -0.66
    izons
    -0.66
    picture
    -0.66
    quit
    -0.65
    POSITIVE LOGITS
     probable
    0.73
     unanimously
    0.69
     unclear
    0.67
     timet
    0.64
     ¶
    0.63
     raining
    0.62
     incorrectly
    0.62
     orally
    0.62
     Engels
    0.61
     incidentally
    0.61
    Activations Density 0.108%

    No Known Activations