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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
    11. 24007
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    Explanations

    terms related to various processes such as procurement, storage, distribution, sale, and marketing, as well as specific items like poultry

    oai_token-act-pair · gpt-3.5-turbo

    terms related to supply chain and production processes

    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
    20439
    -0.68
     Pixie
    -0.54
    士
    -0.54
    innon
    -0.52
    available
    -0.51
    iggurat
    -0.51
     suffice
    -0.51
    é¾į
    -0.51
    ERO
    -0.51
    ggle
    -0.50
    POSITIVE LOGITS
    wise
    0.54
    aila
    0.53
     apologies
    0.51
    etheless
    0.50
     boycot
    0.49
    letes
    0.47
    jack
    0.46
    cffff
    0.45
    entimes
    0.45
    Nav
    0.44
    Activations Density 1.359%

    No Known Activations