: It suppresses or identifies specific output tokens, acting as a filter within the model's decision-making process.
: In academic literature, the range ending in 124095 is cited in discussions regarding Dilated CNN models for image classification tasks. 124095
In the context of machine learning and neural networks, identifies a specific "feature" or SAE (Sparse Autoencoder) latent within the Gemma 2 9b (IT) model, specifically in the 20-GEMMASCOPE-RES-131K layer. Feature 124095: Negative Logits : It suppresses or identifies specific output tokens,
This feature is a computational "neuron" that activates in response to specific linguistic patterns. According to Neuronpedia , its primary function is associated with for specific characters or tokens. Feature 124095: Negative Logits This feature is a
: It is often analyzed alongside other similar features within the Gemma Scope to understand how the model represents complex concepts or steers its own internal logic. Other Technical References
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Last Updated: Mar 9th, 2026
: It suppresses or identifies specific output tokens, acting as a filter within the model's decision-making process.
: In academic literature, the range ending in 124095 is cited in discussions regarding Dilated CNN models for image classification tasks.
In the context of machine learning and neural networks, identifies a specific "feature" or SAE (Sparse Autoencoder) latent within the Gemma 2 9b (IT) model, specifically in the 20-GEMMASCOPE-RES-131K layer. Feature 124095: Negative Logits
This feature is a computational "neuron" that activates in response to specific linguistic patterns. According to Neuronpedia , its primary function is associated with for specific characters or tokens.
: It is often analyzed alongside other similar features within the Gemma Scope to understand how the model represents complex concepts or steers its own internal logic. Other Technical References