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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. 10-RES-JB
    11. 8500
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    Explanations

    keywords related to cultivation, farming, and growing plants

    oai_token-act-pair · gpt-3.5-turbo

    terms related to cultivation and production

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    zzi
    -0.76
    uyomi
    -0.69
    ensional
    -0.67
    oute
    -0.67
    duty
    -0.65
     Mub
    -0.65
     911
    -0.65
    ux
    -0.64
    ciplinary
    -0.64
    PLIC
    -0.62
    POSITIVE LOGITS
     vegetables
    1.08
     crops
    1.03
     trees
    0.92
     vines
    0.91
     hemp
    0.91
     tomatoes
    0.90
     veggies
    0.90
     plants
    0.88
     gardens
    0.87
     pains
    0.86
    Activations Density 0.058%

    No Known Activations