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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. 0-RES-JB
    6. 15
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    INDEX
    Explanations

    terms related to achieving peak performance or reaching maximum levels

    oai_token-act-pair · gpt-3.5-turbo

    terms related to highs and lows in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    DI
    -0.74
     subclass
    -0.71
    armed
    -0.69
    rib
    -0.64
    edia
    -0.64
    page
    -0.63
     Wing
    -0.62
    va
    -0.62
     automatically
    -0.62
    cha
    -0.59
    POSITIVE LOGITS
     highs
    4.24
     lows
    3.41
     peaks
    1.79
     heights
    1.45
     positives
    1.35
     ups
    1.27
     extremes
    1.22
     dips
    1.21
     ceilings
    1.17
     milestones
    1.16
    Activations Density 0.014%

    No Known Activations