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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. 11-RES-JB
    11. 5703
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    Explanations

    words related to cooking instructions, such as cutting, slicing, dicing, and forming

    oai_token-act-pair · gpt-3.5-turbo

    cooking instructions related to food preparation and cutting techniques

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    door
    -0.71
     privilege
    -0.68
     Contrast
    -0.65
     Rent
    -0.64
    orship
    -0.64
    irens
    -0.64
    nikov
    -0.62
     Invest
    -0.61
    visor
    -0.61
    emia
    -0.61
    POSITIVE LOGITS
     manageable
    1.54
     cubes
    1.28
     chunks
    1.27
     shapes
    1.16
     pieces
    1.15
     slices
    1.13
     cylinders
    1.09
     strips
    1.08
     halves
    1.08
     triangles
    1.08
    Activations Density 0.278%

    No Known Activations