Create README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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tags:
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- mechanistic interpretability
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- sparse autoencoder
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- llama
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- llama-3
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---
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## Model Information
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A SAE (Sparse Autoencoder) for [deepseek-ai/DeepSeek-R1-Distill-Llama-70B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-70B).
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It is trained specifically on layer 48 of DeepSeek-R1-Distill-Llama-8B and achieves a final L0 of 36.
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This model is used to decompose Llama's activations into interpretable features.
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The SAE weights are released under Apache, however DeepSeek-R1-Distill-Llama-70B is to be used under Meta's Llama 3 License.
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## How to use
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A Jupyter Notebook is provided to test the model
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<a target="_blank" href="https://colab.research.google.com/github/qrsch/SAE/blob/main/SAE.ipynb">
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab", width="200px"/>
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</a>
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## Training
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Our SAE was trained using [LMSYS-Chat-1M dataset](https://arxiv.org/pdf/2309.11998) as well as [PrimeIntellect/NuminaMath-QwQ-CoT-5M](https://huggingface.co/datasets/PrimeIntellect/NuminaMath-QwQ-CoT-5M).
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## Acknowledgements
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This release wouldn't have been possible without the work of [Goodfire](https://www.goodfire.ai/) and [Anthropic](https://transformer-circuits.pub/)
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A huge thank goes to [runpod](https://www.runpod.io/), who generously sponsored the compute for this run!
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```
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```
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