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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. 865
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    Explanations

    phrases related to learning and extracting lessons from experiences

    oai_token-act-pair · gpt-3.5-turbo

    constructions that reference the act of learning from experiences or observations

    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
    ahan
    -0.66
    gui
    -0.66
    exclusive
    -0.65
    achable
    -0.62
    amation
    -0.60
     curtains
    -0.60
    YE
    -0.59
    owl
    -0.58
    istent
    -0.58
     excluded
    -0.58
    POSITIVE LOGITS
     firsthand
    0.95
    Pract
    0.84
    Format
    0.78
     Teach
    0.76
    DragonMagazine
    0.75
    ERY
    0.74
    çīĪ
    0.70
    format
    0.69
     Drill
    0.68
     skills
    0.67
    Activations Density 0.233%

    No Known Activations