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Awesome GitHub RepositoriesNormalization Interception
Wrapping normalization layers with hooks to monitor and modify internal states.
Distinct from Normalization Layers: Focuses on the interceptability of normalization layers for research, not the implementation of the normalization itself.
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Awesome Normalization Interception GitHub Repositories
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- transformerlensorg/transformerlens
TransformerLensOrg/TransformerLens
3,098Ver en GitHubTransformerLens is a library for mechanistic interpretability research designed to reverse engineer the learned algorithms within large language models. It provides a standardized framework for wrapping diverse transformer architectures, allowing researchers to extract, manipulate, and analyze internal activations and weights through a consistent interface. The project distinguishes itself through a comprehensive system of activation hooks that can capture, patch, and ablate internal tensors during the forward pass. It includes specialized utilities for decomposing fused projections, material
Wraps model normalization layers with standardized hooks for accessing and modifying internal activations.
Python
