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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. 4-RES-JB
    11. 833
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    Explanations

    references to cameras or surveillance equipment

    oai_token-act-pair · gpt-3.5-turbo

    references to cameras and surveillance

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

    No Comments

    Negative Logits
    emonic
    -0.82
    querque
    -0.72
    heit
    -0.70
    contract
    -0.67
    tions
    -0.67
    hend
    -0.66
    rust
    -0.65
    wegian
    -0.65
    ithub
    -0.64
    pend
    -0.63
    POSITIVE LOGITS
     Camer
    1.15
     cameras
    1.12
     camera
    0.99
     pans
    0.99
     microphones
    0.98
     shutter
    0.89
     footage
    0.86
     Nikon
    0.85
     Operator
    0.83
     Camera
    0.82
    Activations Density 0.020%

    No Known Activations