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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. 5-RES-JB
    6. 10758
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    Explanations

    actions related to eating

    oai_token-act-pair · gpt-3.5-turbo

    actions related to eating and social interactions

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    pects
    -0.63
    Reviewer
    -0.62
     Timeline
    -0.61
    ocus
    -0.58
    etheless
    -0.56
     RELE
    -0.55
    NetMessage
    -0.55
    spective
    -0.54
     nutshell
    -0.54
     notably
    -0.54
    POSITIVE LOGITS
     toilet
    0.67
     refill
    0.64
     snack
    0.63
     washing
    0.62
     chewing
    0.62
     saline
    0.60
     toilets
    0.60
     cig
    0.60
     drink
    0.60
     dye
    0.58
    Activations Density 2.489%

    No Known Activations