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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. 9-RES-JB
    6. 6623
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    Explanations

    references to measurements involving height and weight

    oai_token-act-pair · gpt-3.5-turbo
    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
     swearing
    -0.65
     Goodman
    -0.63
     Cutter
    -0.61
     prominence
    -0.60
    brance
    -0.59
     descending
    -0.59
    idence
    -0.58
     embarrassment
    -0.58
     unpre
    -0.58
     Lauder
    -0.58
    POSITIVE LOGITS
    90
    1.39
    96
    1.37
    76
    1.35
    86
    1.35
    87
    1.31
    89
    1.30
    82
    1.29
    62
    1.29
    63
    1.29
    85
    1.28
    Activations Density 0.188%

    No Known Activations