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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. 1-RES-JB
    11. 14345
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    Explanations

    mentions of bandwidth and throughput metrics

    oai_token-act-pair · gpt-3.5-turbo

    terms related to network bandwidth and throughput

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 1-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.1.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.1.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    1
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Kubrick
    -0.73
    oan
    -0.72
    neys
    -0.69
    inse
    -0.69
     Martinez
    -0.68
    tail
    -0.67
    ten
    -0.66
     Garfield
    -0.65
    NEY
    -0.64
     Bain
    -0.64
    POSITIVE LOGITS
     bandwidth
    1.39
    width
    0.92
     throughput
    0.89
     optimizations
    0.84
     utilization
    0.81
     allocations
    0.80
    velength
    0.79
     aperture
    0.79
     connectivity
    0.79
     latency
    0.79
    Activations Density 0.009%

    No Known Activations