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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. 2-RES-JB
    6. 17985
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    INDEX
    Explanations

    the word "observers" with high activation values

    oai_token-act-pair · gpt-3.5-turbo

    mentions of observers or observational roles

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 2-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.2.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.2.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    2
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    street
    -0.67
    eways
    -0.67
    Hom
    -0.67
    False
    -0.66
    Enough
    -0.63
    rax
    -0.62
    Bio
    -0.62
    sis
    -0.62
    Customer
    -0.62
    eating
    -0.61
    POSITIVE LOGITS
     observers
    1.28
     observer
    1.22
     wat
    1.03
    acers
    0.92
     observing
    0.87
    auts
    0.82
    opol
    0.81
     onlook
    0.79
     "$:/
    0.78
     rejoice
    0.78
    Activations Density 0.013%

    No Known Activations