Transformer Lens Interpretability
원문: transformer-lens-interpretability
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching e
무엇을 하나요
TransformerLens: Mechanistic Interpretability for Transformers TransformerLens is the de facto standard library for mechanistic interpretability research on GPT style language models. Created by Neel Nanda and maintained by Bryce Meyer, it provides clean interfaces to inspect and manipulate model internals via HookPoints on every activation. GitHub : [TransformerLensOrg/TransformerLens](https://github.com/TransformerLensOrg/TransformerLens) (2,900+ stars) When to Use TransformerLens Use TransformerLens when you need to: Reverse engineer algorithms learned during training Perform activation patching / causal tracing experiments Study attention patterns and information flow Analyze circuits (e…
실행 시 본인 API 키(BYOK)로 동작하며, 모델 비용은 사용자 계정에서 직접 결제됩니다.