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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. 1-RES-JB
    6. 4560
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    INDEX
    Explanations

    adjectives related to intensity or depth, particularly negative emotions like concern, sadness, and offense

    oai_token-act-pair · gpt-3.5-turbo

    intense expressions of concern or distress

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    othy
    -0.80
     Millennium
    -0.80
    amins
    -0.77
    oras
    -0.75
    ioch
    -0.75
    ordan
    -0.75
    orio
    -0.74
    iton
    -0.70
    culosis
    -0.69
    arters
    -0.69
    POSITIVE LOGITS
     deeply
    0.96
     entrenched
    0.95
     ingrained
    0.92
     aroused
    0.90
     seated
    0.87
     rooted
    0.86
     enough
    0.85
     penetrating
    0.85
     immersed
    0.83
     embedded
    0.83
    Activations Density 0.008%

    No Known Activations