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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. 3-RES-JB
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    Explanations

    food-related terms

    oai_token-act-pair · gpt-3.5-turbo

    references to various types of foods, particularly in the context of health and diet

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Riders
    -0.72
     Dhabi
    -0.72
    ño
    -0.68
     Bots
    -0.66
     Gib
    -0.65
     Saud
    -0.63
     PV
    -0.63
     Blades
    -0.62
     Lash
    -0.61
     Warsaw
    -0.61
    POSITIVE LOGITS
     foods
    1.11
     eaten
    1.00
    eteria
    0.90
    paste
    0.85
    nect
    0.85
     ingested
    0.83
     fats
    0.82
     starch
    0.81
     carbohydrates
    0.81
     eater
    0.81
    Activations Density 0.025%

    No Known Activations