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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. 3-RES-JB
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    Explanations

    mentions of steak cuts and preparation methods

    oai_token-act-pair · gpt-3.5-turbo

    references to steak and related culinary terms

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 3-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.3.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.3.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    3
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inators
    -0.64
     Citizens
    -0.64
    agnetic
    -0.64
    phas
    -0.64
    perse
    -0.63
     Constable
    -0.63
    pher
    -0.61
    pheus
    -0.61
     Commonwealth
    -0.60
     gearing
    -0.60
    POSITIVE LOGITS
     steak
    1.13
     knives
    0.89
    becue
    0.86
     dinner
    0.83
    worms
    0.82
     dinners
    0.81
     knife
    0.80
    chnology
    0.79
    erie
    0.79
    \\\\\\\\
    0.79
    Activations Density 0.012%

    No Known Activations