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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. 9-RES-JB
    11. 1853
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    Explanations

    spefiic academic or athletic years, particularly focusing on the classification of students based on their progress in education or sports

    oai_token-act-pair · gpt-3.5-turbo

    references to academic classifications and years in school

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ichick
    -0.99
    ioned
    -0.81
    abulary
    -0.81
    rosis
    -0.77
    è¦ļéĨĴ
    -0.73
    stretched
    -0.71
    igree
    -0.71
    pots
    -0.70
    closed
    -0.70
    pel
    -0.69
    POSITIVE LOGITS
     dorm
    0.98
     soph
    0.91
     college
    0.89
     slump
    0.87
    omore
    0.87
     Soph
    0.86
     classmate
    0.86
     enrollment
    0.85
    arsity
    0.85
     semester
    0.85
    Activations Density 0.047%

    No Known Activations