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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 9-RES-JB
    11. 6977
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    Explanations

    phrases related to planning, coordination, and execution of tasks or projects

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to goal achievement and strategic planning

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Torrent
    -0.72
     Cosponsors
    -0.68
     unfocusedRange
    -0.65
    illin
    -0.63
     Courtesy
    -0.63
     mentioning
    -0.61
    toggle
    -0.59
    Streamer
    -0.59
     smelled
    -0.59
     Patreon
    -0.58
    POSITIVE LOGITS
     desired
    0.96
     worthwhile
    0.96
     optimal
    0.93
     successful
    0.90
     safely
    0.90
     success
    0.89
     succeeding
    0.89
     optimum
    0.89
     achieve
    0.87
     eventual
    0.87
    Activations Density 0.746%

    No Known Activations