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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. 17350
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    INDEX
    Explanations

    words related to instructions or directions

    oai_token-act-pair · gpt-3.5-turbo

    elements related to improving quality and communication

    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
    illon
    -0.75
     caveats
    -0.57
     stunts
    -0.56
     consists
    -0.56
    ARI
    -0.56
     negatives
    -0.56
    \/\/
    -0.55
     accelerator
    -0.55
     pits
    -0.54
     suspensions
    -0.54
    POSITIVE LOGITS
     properly
    0.86
     efficiently
    0.76
     uninterrupted
    0.74
     safely
    0.74
    appropriately
    0.72
     freely
    0.71
     appropriately
    0.71
     correctly
    0.70
    rences
    0.70
     smoothly
    0.70
    Activations Density 0.404%

    No Known Activations