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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. 3-RES-JB
    6. 8591
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    Explanations

    By analyzing the activations, this neuron seems to be looking for mentions of unintended or additional outcomes related to actions or events

    oai_token-act-pair · gpt-3.5-turbo

    mentions of "product" and its variations

    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
     Hornets
    -0.62
    ITED
    -0.62
     Warriors
    -0.61
     Panther
    -0.61
     pup
    -0.61
     mosqu
    -0.60
    ARP
    -0.60
    ©¶æ
    -0.60
     coil
    -0.59
     bee
    -0.58
    POSITIVE LOGITS
    ively
    1.19
    iveness
    1.18
    ivity
    1.16
    ions
    1.03
    ivities
    0.98
    ivist
    0.91
    arian
    0.89
    ivism
    0.88
    urer
    0.84
    itute
    0.81
    Activations Density 0.024%

    No Known Activations