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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. 9-RES-JB
    11. 1776
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    Explanations

    food-related items, specifically items that include bacon

    oai_token-act-pair · gpt-3.5-turbo

    references to bacon and related food items

    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
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    No Comments

    Negative Logits
    ept
    -0.85
    cover
    -0.78
    hips
    -0.74
    visors
    -0.71
    eon
    -0.71
    cases
    -0.68
    chenko
    -0.67
    lasses
    -0.66
    Db
    -0.65
    oric
    -0.65
    POSITIVE LOGITS
    nect
    0.94
    halla
    0.88
     grease
    0.84
     chees
    0.78
    agher
    0.75
     bacon
    0.74
     cheese
    0.72
     pardon
    0.72
     borough
    0.71
    netflix
    0.71
    Activations Density 0.109%

    No Known Activations