Jspace Lens Llama8b provides pre-fitted Jacobian Lens matrices for specific large language models, including Qwen2.5-7B-Instruct and Llama-3.1-8B-Instruct. The resource is intended for interpretability research focused on the internal workings of transformer-based models. The included matrices are produced by jspace, described as an open replication of research by Lindsey et al., Anthropic 2026. The Jacobian Lens approach captures how each intermediate layer of a model maps to the final residual stream, enabling analysis of what each layer is "thinking" at a given point without requiring a second model or additional probe training. The matrices are fitted over 1,000 diverse prompts using a fused Hutchinson VJP estimator, and each provided .pt file contains one square matrix per layer, with dimensions matching the model's hidden state size. This setup allows users to load these matrices and inspect the internal representations of the supported models directly. The tool is delivered as downloadable files, specifically .pt files compatible with the relevant model architectures. The license is specified as MIT. The focus on interpretability and mechanistic analysis positions this tool for researchers and practitioners interested in understanding the internal mechanisms of large language models, particularly those working with Llama and Qwen architectures.
In the Foundation models & chat space, Jspace Lens Llama8b takes a focused approach. It focuses on helping AI researchers interpret and analyze the internal representations of large language models using Jacobian Lens matrices. It is built as an open-source project for AI interpretability researchers. Jspace Lens Llama8b is open source under the MIT license. The product ships for the web and the command line, and it can be self-hosted.
It is developed by Kameshr, and the product first shipped in 2026. Development happens publicly on GitHub with 32 commits in the last 90 days. Key capabilities include jacobian lens, model interpretability, and layer analysis.
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