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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. 5064
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    INDEX
    Explanations

    references to police or military training activities

    oai_token-act-pair · gpt-3.5-turbo

    references to training

    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
    osi
    -0.74
    ventory
    -0.71
    portation
    -0.68
    vous
    -0.63
    relative
    -0.63
    aceae
    -0.63
    peria
    -0.62
    ogene
    -0.62
    fff
    -0.60
     sliding
    -0.60
    POSITIVE LOGITS
     Peaks
    0.97
     seminars
    0.85
    UFC
    0.82
     sessions
    0.80
     instructors
    0.80
     manuals
    0.78
     exercises
    0.77
    masters
    0.75
     acad
    0.74
     academy
    0.74
    Activations Density 0.035%

    No Known Activations