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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. 19127
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    Explanations

    references to quantities or values followed by a word or phrase denoting a very large amount

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating high quantities or amounts

    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
    illary
    -0.81
     Lauder
    -0.70
    KE
    -0.69
    arium
    -0.68
    UE
    -0.68
    Ô
    -0.67
    ****************
    -0.67
    ï¸
    -0.66
    UES
    -0.64
    ãĤ´
    -0.63
    POSITIVE LOGITS
    loading
    1.01
    hang
    1.00
    drive
    0.99
    priced
    0.97
    lord
    0.96
    tones
    0.90
    whelming
    0.89
    population
    0.89
    haul
    0.88
    valued
    0.88
    Activations Density 0.103%

    No Known Activations