Sparse Autoencoders
Collection
SAEs are tools for understanding the internal representations of neural networks. These can be loaded using https://github.com/EleutherAI/sae
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6 items
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Updated
These transcoders were trained on the outputs of the first 15 MLPs in deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B. We used 10 billion tokens from FineWeb edu deduped at a context length of 2048. The number of latents is 65,536 and a linear skip connection is included.
Fraction of variance unexplained ranges from 0.01 to 0.37.
Base model
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B