A toolkit for large scale distributed training
Project description
LASER (a toolkit for Large scAle diStributEd tRaining)
A toolkit for large scale distributed training
With LARSER we succeeded to train DeBERTa 1.5B model without model parallelism. The DeBERTa 1.5B model is the SOAT model on GLUE and SuperGLUE leaderboard. And it's the first model that surpass T5 11B model and human performance on SuperGLUE leaderboard.
TODOs
- Add documentation and usage examples
git version: 57143200814583410acdd0c5ac0a0f8bab8a1f7e date: 2021-02-04 09:55:12.622124
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
LASER-0.0.5-py3-none-any.whl
(22.2 kB
view details)
File details
Details for the file LASER-0.0.5-py3-none-any.whl
.
File metadata
- Download URL: LASER-0.0.5-py3-none-any.whl
- Upload date:
- Size: 22.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.25.0 CPython/3.6.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 523847d32ccd26ce703077309e5eddf140cada2290daa12e54d89b6c3ab6f9e4 |
|
MD5 | 3b91d382d87f04453fbab3cdcc3d8ef5 |
|
BLAKE2b-256 | f94afaebd70e479880c507c11d7318dd670416d53b5d6b6b973fd70ce97d72a7 |