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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. 6-RES-JB
    11. 21849
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    Explanations

    mentions of dinner and dining-related activities

    oai_token-act-pair · gpt-3.5-turbo

    references to dinner and related dining events

    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
    ignty
    -0.76
     Archangel
    -0.70
    rity
    -0.65
     Weld
    -0.64
     Aerospace
    -0.63
     Gemini
    -0.62
    vernment
    -0.61
     cannabin
    -0.61
    Offline
    -0.61
    ounty
    -0.61
    POSITIVE LOGITS
     dinner
    1.02
     dinners
    1.01
     meal
    0.96
     supper
    0.96
     meals
    0.95
    eteria
    0.93
     buffet
    0.90
     guests
    0.89
    bowl
    0.87
    worms
    0.84
    Activations Density 0.022%

    No Known Activations