README.md

metadata

license: cc-by-4.0
tags:
  - pytorch
  - albef
  - multitask

Working Albef implementation for Multitask

Overview

A small Albef implementation for Multitask, packaged with an explicit configuration and an initialization checkpoint. The base variant is a reproducible starting point, not a trained model release.

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Quick Check

Run python pipeline.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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Contact

Questions or corrections: open a discussion in this repository.

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Limitations

The checkpoint is untrained and unaudited. Treat the repository as an experimental starting point; anything learned from a future trained version must be documented separately.

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Repository Status

1. Single-file implementation; the __main__ block runs a smoke test.
2. config.json and training_args.json hold the generated settings.
3. model.safetensors is freshly initialized — plumbing, not results.
4. No benchmark numbers are reported on purpose.

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Training Details

1. Framework: PyTorch
2. Precision: fp32
3. Init scheme: xavier
4. Hardware: a single consumer GPU is enough
5. Typical run: minutes, not hours

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Architecture

1. Architecture: Albef
2. Scale: base
3. Attention: linear
4. Fusion: tucker
5. Activation: gelu tanh
6. Normalization: groupnorm

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Default Experiment Recipe

The generated recipe uses lion with a constant warmup 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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Files

1. pipeline.py — primary artifact
2. README.md — this documentation
3. config.json — architecture configuration
4. training_args.json — default experiment settings
5. model.safetensors — initialization checkpoint

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License

Distributed under the cc-by-4.0 license. External datasets keep their own terms — check them separately.