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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. 14580
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    Explanations

    mentions of actions or events happening during a sports game

    oai_token-act-pair · gpt-3.5-turbo

    details related to sports actions and plays

    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
     organisers
    -0.68
    rooms
    -0.66
    csv
    -0.66
    artifacts
    -0.66
    abus
    -0.65
    facts
    -0.64
    equ
    -0.63
    abl
    -0.62
    Admin
    -0.62
    models
    -0.62
    POSITIVE LOGITS
     header
    0.98
     alley
    0.98
     leaping
    0.94
     volley
    0.91
     fastball
    0.90
     interception
    0.87
     jumper
    0.87
     diving
    0.87
     shot
    0.85
     pass
    0.85
    Activations Density 0.120%

    No Known Activations