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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. 23468
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    Explanations

    words related to camping or outdoor activities, with a focus on tents

    oai_token-act-pair · gpt-3.5-turbo

    references to tents or related concepts

    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
    ÃĽ
    -0.68
    EVA
    -0.67
     symmetry
    -0.66
    bye
    -0.64
     congr
    -0.62
    nesota
    -0.61
    Words
    -0.61
    obbies
    -0.60
    Second
    -0.60
     Cuomo
    -0.59
    POSITIVE LOGITS
    atively
    1.34
    acle
    1.29
    pole
    1.21
    acles
    1.02
     encamp
    0.97
     tent
    0.96
     tents
    0.90
    acular
    0.88
     pole
    0.88
     poles
    0.86
    Activations Density 0.015%

    No Known Activations