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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. 5-RES-JB
    6. 1217
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    Explanations

    phrases related to improvement or understanding in various contexts

    oai_token-act-pair · gpt-3.5-turbo

    phrases emphasizing the enhancement or improvement of understanding

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    heter
    -0.66
    mad
    -0.64
    ername
    -0.63
    note
    -0.63
    NetMessage
    -0.63
     Straw
    -0.63
    HO
    -0.63
    itto
    -0.61
    asma
    -0.61
     Dresden
    -0.60
    POSITIVE LOGITS
     acquainted
    0.79
     contextual
    0.78
    anced
    0.77
     understanding
    0.77
     leverage
    0.75
     suited
    0.74
     entreprene
    0.74
     transparency
    0.74
    initions
    0.74
     than
    0.73
    Activations Density 0.055%

    No Known Activations