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README.md
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---
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license: apache-2.0
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tags: [hobbylm, sparse-autoencoder, interpretability, sae]
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---
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# HobbyLM-SAE
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A **top-k Sparse Autoencoder** for mechanistic interpretability of [HobbyLM-Base](https://huggingface.co/rootxhacker/HobbyLM-Base).
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It decomposes the residual stream after **layer 8** into a sparse, overcomplete dictionary of
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**12288 features** (32 active per token), most of them human-interpretable
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(12257 auto-labeled by their top-activating tokens).
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## Files
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- `sae.safetensors` — the SAE weights (`W_enc`, `W_dec`, `b_enc`, `b_dec`).
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- `labels.json` — per-feature auto-derived label + example top-activating tokens.
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- `meta.json` — layer, activation scale, base-model run, and SAE config.
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Reconstructs ~97% of the activation variance at L0=32. Reference code + training harness:
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<https://github.com/harishsg993010/HobbyLM> (`hobbylm/sae.py`, `training/modal_sae.py`). Apache-2.0.
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