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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. 2724
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    Explanations

    phrases related to data processing, system performance, and workload management

    oai_token-act-pair · gpt-3.5-turbo

    terms related to workload and workflow management

    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
    ohyd
    -0.79
    ohydrate
    -0.78
    fing
    -0.73
    emn
    -0.71
    ogun
    -0.70
    ruption
    -0.68
    astern
    -0.68
    rupt
    -0.67
    agra
    -0.65
    igning
    -0.65
    POSITIVE LOGITS
     workload
    0.93
     workflow
    0.88
    s
    0.87
    tops
    0.83
    flows
    0.82
    iencies
    0.80
    TPS
    0.79
    sheet
    0.76
     sched
    0.71
    sers
    0.69
    Activations Density 0.011%

    No Known Activations