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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. 11-RES-JB
    6. 15070
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    Explanations

    terms related to technology and materials science, specifically focusing on surface area, efficiency, strength, and resistance

    oai_token-act-pair · gpt-3.5-turbo

    technical terms related to performance and efficiency metrics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    arians
    -0.71
    atre
    -0.65
    ovie
    -0.63
     haunt
    -0.62
    ozy
    -0.62
    anamo
    -0.61
    rius
    -0.61
    IRC
    -0.60
    entious
    -0.59
     Shy
    -0.59
    POSITIVE LOGITS
     characteristics
    1.14
     coefficient
    1.12
     capability
    1.09
     ratio
    1.03
     efficiency
    1.03
     ratios
    0.98
     capabilities
    0.98
     achievable
    0.97
     qualities
    0.96
     Stability
    0.96
    Activations Density 0.216%

    No Known Activations