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license: mpl-2.0
tags:
- pytorch
- hybrid
- multitask
- wip
- prototype
---
# 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.json` and `training_args.json` hold the generated settings.
+ `model.safetensors` is freshly initialized — 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.py` — primary artifact
+ `README.md` — this documentation
+ `config.json` — architecture configuration
+ `training_args.json` — default experiment settings
+ `model.safetensors` — 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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