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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. 9185
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    Explanations

    locations or venues in sports events

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "at" in various contexts

    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
    FTWARE
    -0.68
    itarian
    -0.68
    aceutical
    -0.62
    alpha
    -0.62
     Employees
    -0.61
    photo
    -0.61
    INESS
    -0.61
    idav
    -0.61
     Customers
    -0.60
    erness
    -0.60
    POSITIVE LOGITS
     halftime
    1.21
     least
    1.06
     midfield
    0.86
     fullback
    0.86
     home
    0.86
    las
    0.85
     Wembley
    0.84
    onement
    0.82
    letico
    0.81
     variance
    0.80
    Activations Density 0.119%

    No Known Activations