deepspeedai
@deepspeedai • Open source projects from deepspeedai. Use this route to separate flagship concentration from portfolio breadth before you treat a publisher as broadly strong.
Portfolio concentration
96%
Top three share
Shows whether the organization is driven by one breakout repo or several visible projects.
Breadth
6 repos
Visible snapshot
2 repositories updated in the last 90 days.
Leading language
Python
Portfolio mix
Python (5), C++ (1)
Average size
9K
Stars per repository
Useful for distinguishing one flagship-heavy publisher from a repeatable portfolio.
Updated: 2025-03-26(445d ago)GitHub API fallback6 repositories
96%
of the visible star count comes from this organization's top three repositories.
9K
stars per repository in this same snapshot.
Python
is the most common language here, with 2 repositories updated in the last 90 days.
Why this rank
This organization stands out because one flagship repo drives 79% of its visible star count.
Flagship share 79%Breakout repo: DeepSpeed
Organization pages work best when you separate portfolio breadth from flagship concentration. In deepspeedai's case, the visible top three repositories account for about 96% of total stars in this snapshot, which helps explain whether the organization is known for one breakout project or for a broader repeatable portfolio.
The dominant language mix here is Python (5), C++ (1). That makes this page useful not just for popularity checks, but also for seeing what technical shape an organization's public ecosystem actually has.
Top Repositories
| # | Repository | Language | Stars | 🍴 Forks | Updated |
|---|---|---|---|---|---|
| 1 | deepspeedai/DeepSpeed DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. | Python | 42.5K | 4.9K | Today |
| 2 | deepspeedai/DeepSpeedExamples Example models using DeepSpeed | Python | 6.8K | 1.1K | 3 weeks ago |
| 3 | deepspeedai/Megatron-DeepSpeed Ongoing research training transformer language models at scale, including: BERT & GPT-2 | Python | 2.3K | 365 | 10 months ago |
| 4 | deepspeedai/DeepSpeed-MII MII makes low-latency and high-throughput inference possible, powered by DeepSpeed. | Python | 2.1K | 191 | 11 months ago |
| 5 | deepspeedai/DeepSpeed-Kernels | C++ | 75 | 19 | 1 years ago |
| 6 | deepspeedai/deepspeed-gpt-neox An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library. | Python | 21 | 4 | 3 years ago |
Next step after the organization read
Open a flagship repository, compare a couple of portfolio leaders, or return to the organization map when you want a broader concentration read.
Learn and methodology
Keep trust-building context reachable, but behind the first data read instead of ahead of it.
How to read this organization snapshot
Total stars are useful as a discovery signal, but they do not tell you whether a team maintains every repository equally. Pair this page with release cadence, maintainer activity, and the flagship concentration shown above before making adoption decisions.
For broader background on GitStar's ranking logic and editorial guidance, see Methodology & Editorial Standards.