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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. 13624
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    Explanations

    large numerical values

    oai_token-act-pair · gpt-3.5-turbo

    quantitative data, specifically numbers and their frequency

    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
     curls
    -0.62
     optics
    -0.59
     dogma
    -0.59
     distances
    -0.58
     travels
    -0.58
     routines
    -0.57
     heights
    -0.57
     behavi
    -0.57
     surfaces
    -0.57
     piety
    -0.57
    POSITIVE LOGITS
    000
    1.42
    500
    1.07
    700
    1.06
    09
    1.06
    447
    1.03
    600
    1.03
    528
    1.03
    06
    1.03
    07
    1.02
    900
    1.01
    Activations Density 0.115%

    No Known Activations