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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. 4-RES-JB
    11. 6632
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    oai_token-act-pair · gpt-3.5-turbo

    high activation levels in phrases related to sports and game performance

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

    No Comments

    Negative Logits
    ansk
    -0.81
     censored
    -0.77
     censor
    -0.75
     decrypt
    -0.74
     recognise
    -0.73
     cens
    -0.71
     legally
    -0.70
     suppressed
    -0.70
     censorship
    -0.70
     authorised
    -0.70
    POSITIVE LOGITS
    NBA
    1.11
    Dallas
    1.06
    Coach
    1.06
    ESPN
    1.05
    Players
    1.05
    Game
    1.05
    GAME
    1.04
    Miami
    1.03
    Heat
    1.02
    sports
    1.00
    Activations Density 0.431%

    No Known Activations