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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. 9-RES-JB
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    references to physical training activities

    oai_token-act-pair · gpt-3.5-turbo

    terms related to training and physical preparation activities

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 9-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.9.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.9.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    9
    Activation Function
    relu
    Embeds
    IFrame
    Link
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    Negative Logits
    rin
    -0.70
    ariat
    -0.67
    article
    -0.65
    appy
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    nings
    -0.65
    ãĤ¬
    -0.64
    edia
    -0.63
    nel
    -0.63
     glances
    -0.62
    ppings
    -0.61
    POSITIVE LOGITS
     extensively
    1.09
     alongside
    1.01
     tirelessly
    0.87
     diligently
    0.85
     professionally
    0.84
     against
    0.82
     abroad
    0.81
     miracles
    0.80
     outdoors
    0.80
     furiously
    0.79
    Activations Density 0.188%

    No Known Activations