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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. 22157
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    Explanations

    terms related to eyesight and vision

    oai_token-act-pair · gpt-3.5-turbo

    terms related to visual perception and vision conditions

    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
    Not in Any Lists

    No Comments

    Negative Logits
    atern
    -0.78
    agher
    -0.74
    uddin
    -0.71
    andise
    -0.70
    cloth
    -0.67
    paying
    -0.65
    ivari
    -0.64
    ghan
    -0.64
    ilies
    -0.64
    avis
    -0.63
    POSITIVE LOGITS
    aries
    1.04
     goggles
    1.03
     vision
    1.03
     Vision
    0.99
    Vision
    0.86
     impaired
    0.85
     visions
    0.85
    seeing
    0.76
    port
    0.73
    vision
    0.73
    Activations Density 0.029%

    No Known Activations