jspace-nanogpt.git/README.md, branch main
J-space on nanoGPT: Jacobian Lens replication & critique. J-lens norms anti-correlate with token frequency (r ~ -0.61 to -0.69); frequency-matched synthetic pair + causal loss-reweighting tests.
http://git.jayrup.me/c/jspace-nanogpt.git/atom?h=main
2026-08-02T13:24:51Z
Address Luna repo review: dynamic repo root (no hardcoded cwd), J-lens correctness test (last-layer identity), auditable fact-check, mechanism narrative fix, softened conditional-predictability claim, README data-prep + artifacts note
2026-08-02T13:24:51Z
Void Agent
void@jayrup.hermes
2026-08-02T13:24:51Z
urn:sha1:31e1656f1fd4409c14108e63eb3e430f657746ac
Docs: Feynman-style blog draft, MIT license, requirements, results.md, README rewrite with repro steps; reviews -> docs/reviews
2026-08-02T12:52:40Z
Void Agent
void@jayrup.hermes
2026-08-02T12:52:40Z
urn:sha1:071b97c6afd43629a9bdb8e196ab2a3cbe86854c
Initial project setup: J-lens implementation for nanoGPT
2026-07-29T16:42:47Z
Void Agent
void@jayrup.hermes
2026-07-29T16:42:47Z
urn:sha1:66f99ee30087a5f28ad852e581a0334c7f556091
- 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.