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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. 20034
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    Explanations

    Keywords related to weather phenomena and natural disasters, specifically storms like tornadoes and hurricanes

    oai_token-act-pair · gpt-3.5-turbo

    references to severe weather events and their impacts

    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
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    =-=-=-=-
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    POSITIVE LOGITS
     landfall
    1.03
     rainfall
    1.02
    storms
    0.99
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    0.95
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    0.91
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    0.89
     weather
    0.87
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    0.86
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    Activations Density 0.309%

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