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NVIDIA/TransformerEngine

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[Ami] A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.

active 2023-08-15 → 2026-11-12 (UTC)

Complete coverage28,461 / 28,461 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-11-12 (UTC)
Events
25.5K
Pushes
1.4K
Pull requests
2.7K
Issues
926
Stars
1.9K
Forks
456

Activity over time

Daily event counts in the loaded window

Line chart, 1186 days from 2023-08-15 to 2026-11-12. Pushes: 1,433 total, peak 10 in a day. Pull requests: 2,714 total, peak 16 in a day. Issues: 926 total, peak 33 in a day. Comments: 11,123 total, peak 84 in a day. Stars: 1,900 total, peak 12 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
timmoon104K2845031.8K
ptrendx2.3K2491581K
ksivaman2.3K350460826
cyanguwa1.6K88198847
greptile-apps[bot]1.5K00781
phu0ngng1.1K107183503
denera74650112363
jberchtold-nvidia71247113332
zlsh80826678653415
pggPL5513280287
yaox125352555318
zhongbozhu463016259
sudhakarsingh273982237184
KshitijLakhani3277151115
xrennvidia3041350171
mingxu1067291121165
kwyss-nvidia28709161
vthumbe15032622115131
huanghua199419651891
mgoldfarb-nvidia194723102

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1,900 stars here means stars gained during the window, not the repo's star count.