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| author | Void Agent <void@jayrup.hermes> | 2026-07-29 17:42:47 +0100 |
|---|---|---|
| committer | Void Agent <void@jayrup.hermes> | 2026-07-29 17:42:47 +0100 |
| commit | 66f99ee30087a5f28ad852e581a0334c7f556091 (patch) | |
| tree | b83da26e340a926e6eb46f1b304b66f693a15e81 /train.py | |
Initial project setup: J-lens implementation for nanoGPT
- Core J-lens computation (batched per-layer, per-token gradient method)
- Project README with background and experiment plan
- Sync script for meru Docker container deployment
- Upstream nanoGPT model code copied to src/
Architecture: Computes d(log_p(token))/d(residual_stream) averaged
over corpus contexts, replicating Anthropic's Jacobian Lens technique.
Diffstat (limited to 'train.py')
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