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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. 10-RES-JB
    11. 10162
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    Explanations

    phrases related to meeting specific requirements or standards

    oai_token-act-pair · gpt-3.5-turbo

    phrases related to fulfilling requirements or standards

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.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.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
    rontal
    -0.81
    cloth
    -0.72
    john
    -0.70
    otomy
    -0.70
    cember
    -0.69
    eware
    -0.69
    ectomy
    -0.68
    uese
    -0.67
    utsch
    -0.64
    artifacts
    -0.62
    POSITIVE LOGITS
     expectations
    1.38
     requirements
    1.25
     deadlines
    1.24
     criteria
    1.17
     standards
    1.15
     quotas
    1.10
     stringent
    1.05
     demands
    1.03
    tle
    1.00
     specifications
    0.97
    Activations Density 0.063%

    No Known Activations