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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. 7-RES-JB
    6. 8315
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    INDEX
    Explanations

    phrases or words related to food consumption

    oai_token-act-pair · gpt-3.5-turbo

    references to the action of eating

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 7-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.7.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.7.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    7
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Gemini
    -0.75
     Stellar
    -0.75
    channelAvailability
    -0.72
    worthiness
    -0.72
     Aus
    -0.69
     Stra
    -0.66
     Constable
    -0.65
     Nich
    -0.64
     Lash
    -0.64
     PV
    -0.64
    POSITIVE LOGITS
     habits
    1.02
     eaten
    1.00
     foods
    0.97
    eteria
    0.96
     meals
    0.95
     eat
    0.95
     breakfast
    0.94
    anut
    0.85
     lunch
    0.85
     nutrit
    0.85
    Activations Density 0.029%

    No Known Activations