github
/
ColossalAI
mirror of https://github.com/hpcaitech/ColossalAI
1
0
Fork 0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '935346430f'
${ noResults }
ColossalAI/examples/tutorial/opt/inference/script/process-opt-175b
History
BoxiangW ca6e75bc28
[tutorial] edited hands-on practices (#1899) 		2 years ago
..
README.md [tutorial] edited hands-on practices (#1899) 2 years ago
convert_ckpt.py [tutorial] edited hands-on practices (#1899) 2 years ago
flat-meta.json [tutorial] edited hands-on practices (#1899) 2 years ago
unflat.sh [tutorial] edited hands-on practices (#1899) 2 years ago

README.md

Process OPT-175B weights

You should download the pre-trained weights following the doc before reading this.

First, install metaseq and git clone https://github.com/facebookresearch/metaseq.git.

Then, cd metaseq.

To consolidate checkpoints to eliminate FSDP:

bash metaseq/scripts/reshard_mp_launch_no_slurm.sh <directory_where_all_the_shards_are>/checkpoint_last <output_dir>/ 8 1

You will get 8 files in <output_dir>, and you should have the following checksums:

7e71cb65c4be784aa0b2889ac6039ee8  reshard-model_part-0-shard0.pt
c8123da04f2c25a9026ea3224d5d5022  reshard-model_part-1-shard0.pt
45e5d10896382e5bc4a7064fcafd2b1e  reshard-model_part-2-shard0.pt
abb7296c4d2fc17420b84ca74fc3ce64  reshard-model_part-3-shard0.pt
05dcc7ac6046f4d3f90b3d1068e6da15  reshard-model_part-4-shard0.pt
d24dd334019060ce1ee7e625fcf6b4bd  reshard-model_part-5-shard0.pt
fb1615ce0bbe89cc717f3e5079ee2655  reshard-model_part-6-shard0.pt
2f3124432d2dbc6aebfca06be4b791c2  reshard-model_part-7-shard0.pt

Copy flat-meta.json to <output_dir>.

Then cd to this dir, and we unflatten parameters.

bash unflat.sh <output_dir>/ <new_output_dir>/

Finally, you will get 8 files in <new_output_dir> with following checksums:

6169c59d014be95553c89ec01b8abb62  reshard-model_part-0.pt
58868105da3d74a528a548fdb3a8cff6  reshard-model_part-1.pt
69b255dc5a49d0eba9e4b60432cda90b  reshard-model_part-2.pt
002c052461ff9ffb0cdac3d5906f41f2  reshard-model_part-3.pt
6d57f72909320d511ffd5f1c668b2beb  reshard-model_part-4.pt
93c8c4041cdc0c7907cc7afcf15cec2a  reshard-model_part-5.pt
5d63b8750d827a1aa7c8ae5b02a3a2ca  reshard-model_part-6.pt
f888bd41e009096804fe9a4b48c7ffe8  reshard-model_part-7.pt