DeiT experiments: Generation

Overview

A research-oriented DeiT prototype targeting Generation. The included nano setup documents defaults and file formats without presenting unverified performance numbers.

Quick Check

python predict.py --help

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.

Contact

Questions or corrections: open a discussion in this repository.

Training Details

Item	Value
Framework	PyTorch
Precision	fp32
Init scheme	xavier uniform
Hardware	a single consumer GPU is enough
Typical run	minutes, not hours

Limitations

The initialization checkpoint has not been trained or audited for robustness, fairness, or domain transfer. The implementation should be treated as an experimental starting point. Results from a future trained checkpoint must be documented separately from the defaults shipped here.

Default Experiment Recipe

The included configuration uses sgd with a constant warmup schedule. These are starting values in the script, not evidence of a completed run. For a meaningful evaluation, train all baselines with the same data exposure, tuning budget, and random seeds.

Architecture

Item	Value
Architecture	DeiT
Scale	nano
Attention	multi query
Fusion	tucker
Activation	swish
Normalization	scalenorm

Repository Status

1. The Python file contains the model and runnable example or training entry point.
2. config.json records the generated architecture settings.
3. training_args.json records the default experiment recipe.
4. model.safetensors is a valid initialization checkpoint for smoke tests; it is not presented as a trained benchmark checkpoint.
5. No benchmark score is claimed in this repository.

Files

File	Purpose
predict.py	primary artifact
README.md	this documentation
config.json	architecture configuration
training_args.json	default experiment settings
model.safetensors	initialization checkpoint

License

Released under apache-2.0. Review the source-data terms separately when this repository is used with external datasets.