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license: apache-2.0
tags:
- pytorch
- dino
- multitask
- wip
- smoke-test
---
# Dino for Multitask
## Overview
Working implementation of **Dino** for **Multitask** using a **tiny** configuration. The repository focuses on transparent code and repeatable smoke tests; benchmark claims are deliberately omitted.
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## Acknowledgments
This repo borrows ideas freely from public reference implementations; credit to their authors.
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## 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.
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## 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
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## Environment
| Item | Value |
|---|---|
| Python | >= 3.9 |
| torch | 2.x |
| safetensors | any recent |
| transformers | optional, for loaders |
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## Default Experiment Recipe
The generated recipe uses lion 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.
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## Quick Check
Run `python train.py --help` for the built-in smoke test. Because this is a custom implementation, generic automatic loading APIs require an explicit adapter before use.
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## Files
| File | Purpose |
|---|---|
| `train.py` | primary artifact |
| `README.md` | this documentation |
| `config.json` | architecture configuration |
| `training_args.json` | default experiment settings |
| `model.safetensors` | initialization checkpoint |
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## License
Distributed under the **apache-2.0** license. External datasets keep their own terms — check them separately.
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