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.


Acknowledgments

This repo borrows ideas freely from public reference implementations; credit to their authors.


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 โ€” plumbing, not results.
  • No benchmark numbers are reported on purpose.

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

Environment

Item Value
Python >= 3.9
torch 2.x
safetensors any recent
transformers optional, for loaders

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.


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.


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

License

Distributed under the apache-2.0 license. External datasets keep their own terms โ€” check them separately.

Downloads last month
1
Safetensors
Model size
33.1k params
Tensor type
F32
ยท
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support