Mirror of the fleet agent codebase — reusable, config-driven Kaggle agents + their data-wise verifiers — plus the per-competition experiment code built on top of them.
fleet_agents/ — the agents (BaseAgent subclasses): tabular/GBM, geology particle-filter (Track B),
neural-sequence Muon trainer (Track C), low-bit QAT (NVFP4/MXFP4/int8), setup-env GPU guard
(the verified cu128 / CUDA-12.8 sm_120 stack for the RTX 5090), and many more.test_fleet_agents/ — one data-wise verifier per agent (offline, deterministic).competitions/<slug>/ — experiment code + YAML configs we build per competition (no data).Source of truth lives in the biohub competition workspace; this repo is a stable mirror, synced
and committed every 3 hours (only when changes are pending, and only if every .py byte-compiles).
Sync manually: ./sync_and_commit.sh
21 commits
Python
99.4%
Mirror of the fleet agent codebase — reusable, config-driven Kaggle agents + their data-wise verifiers — plus the per-competition experiment code built on top of them.
fleet_agents/ — the agents (BaseAgent subclasses): tabular/GBM, geology particle-filter (Track B),
neural-sequence Muon trainer (Track C), low-bit QAT (NVFP4/MXFP4/int8), setup-env GPU guard
(the verified cu128 / CUDA-12.8 sm_120 stack for the RTX 5090), and many more.test_fleet_agents/ — one data-wise verifier per agent (offline, deterministic).competitions/<slug>/ — experiment code + YAML configs we build per competition (no data).Source of truth lives in the biohub competition workspace; this repo is a stable mirror, synced
and committed every 3 hours (only when changes are pending, and only if every .py byte-compiles).
Sync manually: ./sync_and_commit.sh
21 commits
Python
99.4%