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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. 1392
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    Explanations

    requests or invitations for interaction

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to user engagement and feedback

    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
    Not in Any Lists

    No Comments

    Negative Logits
    ulic
    -0.70
    EStreamFrame
    -0.66
    ãĤ©
    -0.66
    chin
    -0.66
    ãĥ£
    -0.65
    ino
    -0.63
    inas
    -0.63
     Pil
    -0.61
    sbm
    -0.61
     Manip
    -0.61
    POSITIVE LOGITS
     interested
    0.83
     unsure
    0.80
    mbuds
    0.78
     encount
    0.76
     discrepancy
    0.74
     appre
    0.74
    Need
    0.72
     inacc
    0.70
     inquiries
    0.70
    etheless
    0.68
    Activations Density 0.188%

    No Known Activations