c-llm/dev/data
2024-05-22 22:42:37 +00:00
..
data_common.py first draft, apparently this works. needs cleanups, and also we are not yet utilizing the full batch dimension. we actually have to load in multiple examples and fully utilize batch 2024-05-22 19:24:20 +00:00
fineweb.py continued changes for sharded dataloader 2024-05-22 11:59:09 +00:00
hellaswag.py make hellaswag optional eval yay 2024-05-22 22:42:37 +00:00
mmlu.py refactor how we treat datasets, because we're about to have more of them and we don't want them to clutter up root dir etc. this is only step 1, i'm about to refactor a bunch of the dataloading, how the .bin files work and are loaded, how the DataLoader works, etc. This is all needed to support good evals and training at scale 2024-05-20 22:43:40 +00:00
README.md i also forgot to include the readme file for the new dev/data dir 2024-05-20 23:13:42 +00:00
tinyshakespeare.py the write_datafile function accepts python list, which i think is faster but i didn't check 2024-05-21 17:55:56 +00:00
tinystories.py the write_datafile function accepts python list, which i think is faster but i didn't check 2024-05-21 17:55:56 +00:00

dev/data organization

The idea is that each dataset has a .py file here in the root of dev/data, and each dataset then creates a directory here, and writes and caches anything inside that directory. So for example:

  • running python tinystories.py will create a directory tinystories with its .bin files inside it
  • running python tinyshakespeare.py will create a directory tinyshakespeare with its .bin files inside it

And so on. This way we can nicely organize multiple datasets here, share common utilities between them, and then point the .py/.c code in the root of the project accordingly to these.