Hybrid experiments: Multitask
Overview
This repository is a compact, custom PyTorch implementation of Hybrid for Multitask. The small configuration is intended for code review, smoke tests, and small controlled experiments rather than as a production-ready pretrained release.
Feedback on the structure is welcome; the code is intentionally short.
Repository Status
- Single-file implementation; the
__main__block runs a smoke test. config.jsonandtraining_args.jsonhold the generated settings.model.safetensorsis freshly initialized โ plumbing, not results.- No benchmark numbers are reported on purpose.
Quick Check
Run python model.py --help for the built-in smoke test. Because this is a custom implementation, generic automatic loading APIs require an explicit adapter before use.
Default Experiment Recipe
The generated recipe uses lamb with a step schedule.
These values exist so the script runs end-to-end. A meaningful experiment needs its own tuning budget and at least three seeds.
Limitations
- weights are random-init, so outputs carry no signal
- robustness, fairness and domain transfer are untested
- the API may change without notice while the design settles
Files
model.pyโ primary artifactREADME.mdโ this documentationconfig.jsonโ architecture configurationtraining_args.jsonโ default experiment settingsmodel.safetensorsโ initialization checkpoint
License
Released under mpl-2.0. Review the source-data terms separately when this repository is used with external datasets.
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