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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. 1-RES-JB
    6. 17043
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    Explanations

    mentions of specific types of containers, particularly cups

    oai_token-act-pair · gpt-3.5-turbo

    references to cups and measurements related to beverages

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Voc
    -0.74
    SPONSORED
    -0.71
    IGHTS
    -0.67
     Generations
    -0.67
    doing
    -0.65
    sight
    -0.64
     gearing
    -0.63
     Giuliani
    -0.63
    ccording
    -0.62
     Violent
    -0.59
    POSITIVE LOGITS
    cakes
    1.69
    cake
    1.49
    cup
    1.42
     cup
    1.26
     cups
    1.18
     Cups
    0.84
    acies
    0.81
    isle
    0.81
    ishable
    0.80
     noodles
    0.80
    Activations Density 0.006%

    No Known Activations