---
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.