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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. 9-RES-JB
    11. 3757
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    Explanations

    code snippets and data points

    oai_token-act-pair · gpt-3.5-turbo

    elements related to code or programming syntax

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    No Comments

    Negative Logits
     Vide
    -0.73
    atform
    -0.70
     Divide
    -0.69
     Manson
    -0.66
     Beg
    -0.64
    iasis
    -0.64
     Dish
    -0.64
     screenings
    -0.61
     Franks
    -0.61
     Overse
    -0.61
    POSITIVE LOGITS
    taboola
    0.91
    main
    0.90
    blank
    0.87
    respective
    0.86
    chance
    0.85
    EStreamFrame
    0.84
    DER
    0.83
    POS
    0.82
    default
    0.80
    dict
    0.80
    Activations Density 0.035%

    No Known Activations