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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. 3-RES-JB
    6. 1085
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    Explanations

    numbers at the end of sentences

    oai_token-act-pair · gpt-3.5-turbo

    numerical identifiers or statistics

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    undai
    -0.95
    entry
    -0.76
    raltar
    -0.75
    perm
    -0.74
    efficients
    -0.72
    otaur
    -0.67
     neighb
    -0.66
    oppy
    -0.66
     millenn
    -0.66
    kered
    -0.65
    POSITIVE LOGITS
    00
    1.02
    50
    0.86
    APH
    0.82
    ¢
    0.78
    oran
    0.78
    44
    0.76
    %-
    0.74
    80
    0.74
    88
    0.73
    345
    0.73
    Activations Density 0.031%

    No Known Activations