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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. 2833
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    Explanations

    quantities or measures of production

    oai_token-act-pair · gpt-3.5-turbo

    quantities or measurements related to production

    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
    ARI
    -0.72
    Parent
    -0.66
    ":[
    -0.65
    writers
    -0.65
    laus
    -0.64
     complicity
    -0.63
    imposed
    -0.62
    FontSize
    -0.62
     Username
    -0.62
    Ö¼
    -0.61
    POSITIVE LOGITS
     usable
    0.95
     batches
    0.89
     results
    0.85
     goods
    0.84
     coherent
    0.84
     payload
    0.84
     quantities
    0.82
     output
    0.78
     product
    0.78
     surplus
    0.77
    Activations Density 0.363%

    No Known Activations