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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. 3-RES-JB
    11. 16715
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    Explanations

    adjectives related to food preparation

    oai_token-act-pair · gpt-3.5-turbo

    terms related to food preparation and ingredient chopping

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    rium
    -0.88
    abilities
    -0.84
     Defenders
    -0.72
    quest
    -0.69
    SPONSORED
    -0.68
    repeat
    -0.67
    role
    -0.65
    ability
    -0.65
    ¥µ
    -0.65
    sche
    -0.64
    POSITIVE LOGITS
     onions
    0.97
     onion
    0.94
     diced
    0.90
    ÃįÃį
    0.88
     minced
    0.87
     chunks
    0.86
    aneous
    0.83
     garlic
    0.81
    -+-+-+-+
    0.80
     chopped
    0.80
    Activations Density 0.020%

    No Known Activations