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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. 3047
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    Explanations

    references to running events, especially marathons

    oai_token-act-pair · gpt-3.5-turbo

    terms related to marathons and running events

    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
    olia
    -0.74
     Debor
    -0.72
    onom
    -0.71
    pie
    -0.65
    relation
    -0.64
    arial
    -0.63
    amental
    -0.63
    ãĥķãĤ©
    -0.63
    afort
    -0.62
    amn
    -0.61
    POSITIVE LOGITS
     runner
    1.16
     runners
    1.12
     Runner
    1.00
     sprint
    0.96
     jog
    0.96
     endurance
    0.93
     stride
    0.86
     racer
    0.86
    athon
    0.85
     biking
    0.84
    Activations Density 0.113%

    No Known Activations