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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. 9606
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    Explanations

    food-related instructions or activities

    oai_token-act-pair · gpt-3.5-turbo

    mentions and contexts related to food and cooking

    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
    partisan
    -0.75
    vation
    -0.68
     Sutherland
    -0.67
    agonists
    -0.66
    ray
    -0.66
    untary
    -0.65
    代
    -0.64
    Proxy
    -0.63
    htaking
    -0.62
    orah
    -0.61
    POSITIVE LOGITS
     starter
    0.65
     grade
    0.65
    AMY
    0.64
     Origins
    0.63
    emouth
    0.62
     yeast
    0.62
     Everyday
    0.61
     Cooking
    0.61
     WITHOUT
    0.61
     Elys
    0.60
    Activations Density 0.686%

    No Known Activations