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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. 4410
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    Explanations

    words related to foods to be avoided or consumed

    oai_token-act-pair · gpt-3.5-turbo

    references to various types of foods

    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
     Dhabi
    -0.82
     Riders
    -0.76
    ño
    -0.70
     Blades
    -0.69
     Saud
    -0.68
     Bots
    -0.67
     Gib
    -0.65
    unda
    -0.65
     Lash
    -0.65
     Warsaw
    -0.65
    POSITIVE LOGITS
     foods
    1.11
     eaten
    1.09
     ingested
    0.92
     consumed
    0.92
     starch
    0.86
    eteria
    0.85
    isine
    0.84
    paste
    0.84
     additives
    0.84
    stuff
    0.83
    Activations Density 0.025%

    No Known Activations