README.md

metadata

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.