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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. 2-RES-JB
    6. 10875
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    INDEX
    Explanations

    mentions of specific types of structures, specifically buildings

    oai_token-act-pair · gpt-3.5-turbo

    terms related to buildings and construction

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    nir
    -0.79
    ño
    -0.73
    sha
    -0.71
    sen
    -0.69
    owder
    -0.68
    nia
    -0.67
    romeda
    -0.65
    tle
    -0.64
    pas
    -0.64
     Nadu
    -0.64
    POSITIVE LOGITS
     buildings
    1.18
    raper
    1.08
     Buildings
    1.05
    chool
    0.96
     skysc
    0.95
     blocks
    0.91
     erected
    0.89
     complexes
    0.89
     constructed
    0.84
     towers
    0.83
    Activations Density 0.019%

    No Known Activations