c-llm/dev/data
2024-08-13 17:24:15 +00:00
..
data_common.py attempt to fix PR 2024-08-13 02:13:14 +00:00
edu_fineweb.sh add edu fineweb sh download script, change paths to my HF repo, add hellaswag to starter pack 2024-07-01 21:41:15 +00:00
fineweb.py fix tokenizer omg 2024-08-13 17:24:15 +00:00
fineweb.sh add shell script that downloads the .bin files of FineWeb100B directly 2024-06-20 22:39:09 +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 Replace fire with argparse 2024-08-10 22:45:46 +02:00
tinyshakespeare.py fix tokenizer omg 2024-08-13 17:24:15 +00:00
tinystories.py fix tokenizer omg 2024-08-13 17:24:15 +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.

Note: we support "gpt-2" and "llama" (llama 3 in particular) models and the above scripts will tokenize gpt-2 by default.