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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. 3-RES-JB
    6. 1687
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    Explanations

    descriptions highlighting specific aspects of a story or situation

    oai_token-act-pair · gpt-3.5-turbo

    phrases that refer to different aspects or components in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    incinn
    -0.78
    ãĤī
    -0.72
     millenn
    -0.65
    apons
    -0.64
     Klux
    -0.64
    Draft
    -0.64
     confir
    -0.63
    avorite
    -0.63
    ternity
    -0.62
    ministic
    -0.61
    POSITIVE LOGITS
    ials
    0.85
    icular
    0.84
    icularly
    0.81
    icle
    0.78
    ridge
    0.77
    ridges
    0.73
    icles
    0.73
     Myster
    0.72
    ICLE
    0.70
     Payton
    0.69
    Activations Density 0.051%

    No Known Activations