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    1. Home
    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 9-RES-JB
    6. 910
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    Explanations

    mentions or references to manufacturers or products created by manufacturers

    oai_token-act-pair · gpt-3.5-turbo

    references to manufacturers and their products

    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
    mire
    -0.83
    rina
    -0.75
    visor
    -0.69
    mins
    -0.64
     Warden
    -0.64
    ormal
    -0.62
    retion
    -0.62
     sher
    -0.61
     Bagg
    -0.61
    ctica
    -0.59
    POSITIVE LOGITS
     manufactures
    0.87
    ãĤ®
    0.82
     warranties
    0.81
    paces
    0.78
     manufacturers
    0.78
     Electronics
    0.78
    ãĤ´
    0.75
     Warranty
    0.73
     Manufact
    0.72
    è»
    0.72
    Activations Density 0.082%

    No Known Activations