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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. 1982
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    Explanations

    descriptions of different modes of transportation

    oai_token-act-pair · gpt-3.5-turbo

    references to vehicles in various contexts

    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
    wu
    -0.75
     ppm
    -0.75
     pores
    -0.75
    Settings
    -0.73
    parency
    -0.72
     resolutions
    -0.71
     passwords
    -0.70
     hardness
    -0.69
     Diss
    -0.69
    utenberg
    -0.68
    POSITIVE LOGITS
     vehicle
    1.48
     vehicles
    1.37
     SUV
    1.36
     truck
    1.33
     helicopter
    1.33
     cars
    1.30
     wagon
    1.30
     trucks
    1.28
     sedan
    1.28
     aircraft
    1.27
    Activations Density 0.577%

    No Known Activations