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    5. 9-GEMMASCOPE-RES-16K
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    Explanations

    references to services

    oai_token-act-pair · gpt-4o-miniTriggered by @bot

    "services"

    np_acts-logits-general · gemini-2.0-flash

    thinksThe user wants me to explain the behavior of a neuron based on the provided lists: `MAX_ACTIVATING_TOKENS`, `TOKENS_AFTER_MAX_ACTIVATING_TOKEN`, `TOP_POSITIVE_LOGITS`, and `TOP_ACTIVATING_TEXTS`.The explanation needs to be concise (3-20 words), specific, and capture what the neuron detects or predicts by finding patterns. I should avoid starting phrases, capitalization (unless proper noun), and mention of "tokens" or "patterns".Let's analyze the input:- `MAX_ACTIVATING_TOKENS`: Dominated by the word "services" (case variations included).- `TOP_POSITIVE_LOGITS`: Also heavily focused on variations of "services".- `TOP_ACTIVATING_TEXTS`: Contains many phrases like "the services of", "to the services already", "other services", "All services are", "range of services", "Financial Services", "Dubai services", "regulation services", "Accounting", "accounting services", "interactive services", "outlining and describing your services". Many of these relate to offered services by businesses or organizations.- `TOKENS_AFTER_MAX_ACTIVATING_TOKEN`: Includes words like "of", "already", "—", "are", "design", "suitable", "like", ".". This indicates what might follow the mention of "services".The core theme is clearly "services". The neuron seems to activate when the concept of "services" is discussed, particularly in the context of what is offered, provided, or related to a business or organization.Possible explanations:- "offered services"- "business services"- "services provided"- "types of services"- "range of services""services" itself is present in all lists. The `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` suggest contexts like "services of X", "services already Y", "services design", "services suitable for Z", "interactive services".Given the examples, "services of a X", "services already provided", "other services", "All services are", "range of services", "Financial Services", "Dubai services", "regulation services", "accounting services", "interactive services". It seems to capture the general concept of "services" as offerings."services" is the most direct and repeated concept. The examples cover business, technical, financial, and even personal services. The neuron is strongly associated with the word "services" itself.Let's check the length constraint: 3 to 20 words."services" is one word. This is too short.Let's look for a more descriptive phrase.The examples show "services of X", "services already Y", "services design", "services suitable for", "interactive services". The common thread is simply the concept of "services".Perhaps the neuron is just strongly biased towards the word "services" itself, and by extension, concepts related to offerings.If I have to pick a pattern, it's the word "services". But a single word explanation is usually not what's desired if a slightly longer phrase can capture it better.Let's re-examine the `TOP_ACTIVATING_TEXTS`.- "the services of a Sacramento Kings fan favorite."- "to the services already provided by the telnet server."- "and other services — Facebook Messenger, Google Hangouts maybe?"- "All services are carried out on time"- "offers a range of services, including..."- "experience in Financial Services, health and science sector and retail."- "Dubai services design creatively styled wall coverings"- "regulation services are combined with provisioning ecosystem services." offered services

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GEMMA-2-9B-IT @ 9-gemmascope-res-16k
    Configuration
    google/gemma-scope-9b-it-res/layer_9/width_16k/average_l0_88
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
    Features
    16,384
    Data Type
    float32
    Hook Name
    blocks.9.hook_resid_post
    Hook Layer
    9
    Architecture
    jumprelu
    Context Size
    1,024
    Dataset
    monology/pile-uncopyrighted
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Inscrivez
    -0.52
     Cientí
    -0.47
     plegable
    -0.44
     wrongs
    -0.42
     wrong
    -0.41
     jagung
    -0.41
     dourado
    -0.40
    wrong
    -0.40
     big
    -0.39
     mochila
    -0.39
    POSITIVE LOGITS
     services
    1.64
     Services
    1.58
     service
    1.48
    services
    1.46
     SERVICES
    1.45
     Service
    1.45
    Services
    1.44
     SERVICE
    1.34
    service
    1.32
    SERVICES
    1.31
    Activations Density 0.084%

    No Known Activations