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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. 6-RES-JB
    6. 3929
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    Explanations

    instances where the text mentions looking at or examining something closely

    oai_token-act-pair · gpt-3.5-turbo

    phrases that instruct the reader to examine or consider something

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 6-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.6.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.6.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    6
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    HCR
    -0.69
    ¯¯¯¯
    -0.66
    Balt
    -0.65
    burgh
    -0.64
     await
    -0.64
    bery
    -0.62
    blown
    -0.61
    Jr
    -0.61
    ARP
    -0.60
    EMS
    -0.60
    POSITIVE LOGITS
     yourself
    0.75
     google
    0.68
     correctly
    0.66
     lucky
    0.65
    iegel
    0.64
     perpend
    0.63
     minded
    0.61
     math
    0.61
     maths
    0.61
     unlucky
    0.58
    Activations Density 0.179%

    No Known Activations