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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. 0-RES-JB
    11. 459
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    Explanations

    references to individuals being "agents" in various contexts, including literary agents, free agents in sports, FBI agents, and more

    oai_token-act-pair · gpt-3.5-turbo

    references to agents in various contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 0-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.0.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.0.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    0
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    ries
    -0.67
     Built
    -0.66
    pees
    -0.64
     Olympus
    -0.62
     Lunar
    -0.62
    Chall
    -0.61
    mares
    -0.61
    ripp
    -0.60
    stra
    -0.60
     Daylight
    -0.59
    POSITIVE LOGITS
     agent
    4.05
     agents
    3.13
     Agent
    2.87
    agent
    2.82
    Agent
    2.48
     Agents
    2.43
    agents
    2.18
     agency
    1.56
     broker
    1.30
     informant
    1.21
    Activations Density 0.016%

    No Known Activations