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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. 4-RES-JB
    11. 4330
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    Explanations

    details related to buildings, particularly in a context of damage or activity happening within or around a building

    oai_token-act-pair · gpt-3.5-turbo

    references to specific buildings in the context of incidents or events

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

    No Comments

    Negative Logits
    romeda
    -0.86
    opard
    -0.80
    ño
    -0.77
    ï¸ı
    -0.75
    tle
    -0.70
    phal
    -0.70
    sha
    -0.70
     Nadu
    -0.70
    uel
    -0.70
     Chocobo
    -0.69
    POSITIVE LOGITS
    raper
    1.07
     renovations
    0.89
     blocks
    0.88
     occupancy
    0.88
     buildings
    0.87
     erected
    0.86
    building
    0.85
     skysc
    0.81
     apartment
    0.81
    Constructed
    0.81
    Activations Density 0.022%

    No Known Activations