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---
license: apache-2.0
language:
- en
tags:
- mechanistic interpretability
- sparse autoencoder
- llama
- llama-3
---
## Model Information
A SAE (Sparse Autoencoder) for [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B).
It is trained specifically on layer 19 of DeepSeek-R1-Distill-Llama-8B and achieves a final L0 of 93 during training.
This model is used to decompose Llama's activations into interpretable features.
The SAE weights are released under Apache, however DeepSeek-R1-Distill-Llama-8B is to be used under Meta's Llama 3 License.
## How to use
A Jupyter Notebook is provided to test the model
<a target="_blank" href="https://colab.research.google.com/github/qrsch/SAE/blob/main/SAE.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab", width="200px"/>
</a>
## Training
Our SAE was trained using [LMSYS-Chat-1M dataset](https://arxiv.org/pdf/2309.11998).
## Acknowledgements
This release wouldn't have been possible without the work of [Goodfire](https://www.goodfire.ai/) and [Anthropic](https://transformer-circuits.pub/)
A huge thank goes to [runpod](https://www.runpod.io/), who generously sponsored the compute for this run!
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