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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. 9-RES-JB
    6. 8515
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    Explanations

    words related to evaluation or examination processes

    oai_token-act-pair · gpt-3.5-turbo

    terms related to screening and vetting processes

    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
    iev
    -0.78
    orthern
    -0.67
     mortg
    -0.67
     rejoice
    -0.63
    Church
    -0.63
    ince
    -0.61
    stead
    -0.60
    @#&
    -0.59
    utra
    -0.59
    imeo
    -0.58
    POSITIVE LOGITS
     screenings
    1.16
     screening
    1.14
     procedures
    0.87
     screened
    0.82
     vetting
    0.81
    udo
    0.79
     procedure
    0.78
     mamm
    0.78
     scanners
    0.78
     examinations
    0.75
    Activations Density 0.098%

    No Known Activations