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    2. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    3. GPT2-Small
    4. Residual Stream
    5. 5-RES-JB
    6. 20185
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    Explanations

    proper nouns ending in '-que'

    oai_token-act-pair · gpt-3.5-turbo

    instances of the term "que" or related words emphasizing the importance of community or inclusion

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 5-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.5.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.5.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    5
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    inating
    -0.81
    uania
    -0.81
    inately
    -0.77
    iaries
    -0.75
    lessly
    -0.75
    sonian
    -0.73
    inators
    -0.72
    iary
    -0.71
    iband
    -0.70
    omething
    -0.70
    POSITIVE LOGITS
    que
    1.08
    lde
    0.82
    erness
    0.81
    xit
    0.79
    edo
    0.76
    aque
    0.76
    ague
    0.75
    ño
    0.74
    zon
    0.74
    odore
    0.73
    Activations Density 0.014%

    No Known Activations