| ---
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| license: unknown
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| tags:
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| - pytorch
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| - vit
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| - multitask
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| - initialization
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| - smoke-test
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| ---
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|
|
| # ViT experiments: Multitask
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|
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| ## Overview
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|
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| This repository is a compact, custom PyTorch implementation of **ViT** for **Multitask**. The **tiny** configuration is intended for code review, smoke tests, and small controlled experiments rather than as a production-ready pretrained release.
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|
|
| ## Quick check
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|
|
| ```bash
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| python predict.py --help
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| ```
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|
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| Inspect the script's `__main__` block for its generated smoke-test example. Because this is a custom implementation, generic automatic loading APIs require an explicit adapter before use.
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|
|
| ## Acknowledgments
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| Thanks to the maintainers of the open-source libraries this project leans on.
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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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| ## Training details
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|
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| + **Framework**: PyTorch
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| + **Precision**: fp32
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| + **Init scheme**: xavier
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| + **Hardware**: a single consumer GPU is enough
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| + **Typical run**: minutes, not hours
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|
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| ## Default experiment recipe
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|
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| Defaults: **rmsprop** optimizer, **onecycle** schedule. Treat these as starting points; a real run should sweep learning rate and batch size before drawing conclusions.
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|
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| ## Architecture
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|
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| + **Architecture**: ViT
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| + **Scale**: tiny
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| + **Attention**: multi query
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| + **Fusion**: bilinear
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| + **Activation**: swish
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| + **Normalization**: instancenorm
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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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| ## Files
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|
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| + `predict.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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| ## License
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|
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| Released under **unknown**. Review the source-data terms separately when this repository is used with external datasets.
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|
