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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
    11. 13179
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    Explanations

    words related to actions and intentions

    oai_token-act-pair · gpt-3.5-turbo

    phrases indicating desires or intentions related to future actions

    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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    No Comments

    Negative Logits
    hement
    -0.69
    quad
    -0.66
    onz
    -0.62
    =-=-
    -0.62
     MFT
    -0.61
    Chair
    -0.60
     Outbreak
    -0.60
    Hom
    -0.58
     Polic
    -0.57
    hov
    -0.57
    POSITIVE LOGITS
     entail
    0.82
     accomplished
    0.82
     meant
    0.80
     doing
    0.76
    ESA
    0.76
     accomplish
    0.75
     Learned
    0.73
     learnt
    0.73
     glean
    0.71
     entails
    0.69
    Activations Density 0.200%

    No Known Activations