| ---
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| license: apache-2.0
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| tags:
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| - pytorch
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| - dino
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| - multitask
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| - wip
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| - smoke-test
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| ---
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|
|
| # Dino for Multitask
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|
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| ## Overview
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| 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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| ---
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|
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| ## Acknowledgments
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| This repo borrows ideas freely from public reference implementations; credit to their authors.
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|
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| ---
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|
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| ## Repository Status
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|
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| - Single-file implementation; the `__main__` block runs a smoke test.
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| - `config.json` and `training_args.json` hold the generated settings.
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| - `model.safetensors` is freshly initialized — plumbing, not results.
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| - No benchmark numbers are reported on purpose.
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|
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| ---
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|
|
| ## Limitations
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|
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| - weights are random-init, so outputs carry no signal
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| - robustness, fairness and domain transfer are untested
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| - the API may change without notice while the design settles
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|
|
| ---
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|
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| ## Environment
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|
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| | Item | Value |
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| |---|---|
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| | Python | >= 3.9 |
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| | torch | 2.x |
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| | safetensors | any recent |
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| | transformers | optional, for loaders |
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|
|
| ---
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|
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| ## Default Experiment Recipe
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| The generated recipe uses lion with a step schedule.
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| 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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|
|
| ---
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| ## Quick Check
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| 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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|
|
| ---
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|
|
| ## Files
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|
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| | File | Purpose |
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| |---|---|
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| | `train.py` | primary artifact |
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| | `README.md` | this documentation |
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| | `config.json` | architecture configuration |
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| | `training_args.json` | default experiment settings |
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| | `model.safetensors` | initialization checkpoint |
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|
|
| ---
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|
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| ## License
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| Distributed under the **apache-2.0** license. External datasets keep their own terms — check them separately.
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|
