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eliot's Introduction

Eliot - a small large language model

This project is intended for training a language-only transformer using PyTorch. It was started on New Year's Eve 2022.

Significant milestones

  1. Character-level tokenisation and general batching complete (7/1/23).
  2. Minimal model training! (Linear model on char-tokenised data). (8/1/23).
  3. Complete transformer model with positional embeddings (2/3/23).
  4. Minimal single-device training loop on wikitext (13/3/23).

eliot's People

Contributors

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Watchers

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eliot's Issues

Add serialisation to tokeniser

Currently we have to retrain the tokeniser from scratch each time we load it, which takes ~30s for a simple tokeniser on WikiText-103. This isn't too inconvenient but will certainly get longer with more complex tokenisers (which we need).

Adding serialisation should record:

  • Token <-> string mappings
  • Training dataset
  • Training date
  • Vocab size

Add testing

The absence of testing and CI is a pretty glaring omission right now - I'm so used to the Google framework that I've forgotten how to do anything else... Still, I really ought to add good testing - this is an opportunity to see what the best public tools are.

Add serialisation to model.

Currently models can't be saved or loaded, meaning that we can't resume training over multiple instances.

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