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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. 9-RES-JB
    6. 18722
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    INDEX
    Explanations

    descriptions of food production techniques and environmental impact

    oai_token-act-pair · gpt-3.5-turbo

    information related to food production and environmental impact

    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
    VPN
    -0.90
     Explan
    -0.73
    Privacy
    -0.73
     inaction
    -0.71
     Perception
    -0.71
     ACTIONS
    -0.69
     undermin
    -0.69
    IRC
    -0.68
    uyomi
    -0.68
     commenter
    -0.67
    POSITIVE LOGITS
     harvested
    1.34
     harvest
    1.24
     crops
    1.20
     foods
    1.17
     produce
    1.12
     paste
    1.12
     sourced
    1.12
     products
    1.11
     imported
    1.11
     vegetables
    1.10
    Activations Density 0.726%

    No Known Activations