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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. 11-RES-JB
    11. 5481
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    Explanations

    preparation and cooking instructions in a recipe format

    oai_token-act-pair · gpt-3.5-turbo

    numerical values related to cooking times and servings

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 11-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.11.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.11.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    11
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     fuzz
    -0.78
     reinstated
    -0.75
     dynam
    -0.68
     crypt
    -0.68
     extrad
    -0.67
    channelAvailability
    -0.66
     hay
    -0.65
     surg
    -0.64
     unic
    -0.64
     lig
    -0.63
    POSITIVE LOGITS
     Prep
    1.30
     Ingredients
    1.28
     Recipe
    1.04
     Cook
    1.03
    Prep
    1.03
     Serv
    1.03
     Makes
    1.02
     servings
    1.00
     Course
    0.98
     Serving
    0.98
    Activations Density 0.065%

    No Known Activations